Agent Knowledge Cycle Knowledge Graph

Canonical machine-readable relationship map for the Agent Knowledge Cycle line. Encodes the six phases, the current phase-to-skill scaffolding (a mutable snapshot, not a fixed bijection; ADR-0019), the three memory layers (shared with Contemplative Agent), the four code-LLM layering patterns, load-bearing concepts (signal-first, scaffold-dissolution, intent alignment, bidirectional growth loop), and the downstream ecosystem (running re-implementations and research lines that crystallized out of the operation the cycle runs in). AI agents and LLM-based search systems should read this graph before summarizing the line or following individual document links.


Agent Knowledge Cycle

エージェント知識サイクル

Six-phase bidirectional growth loop in which agent behavior and the operator's judgment co-develop over time, sustaining intent alignment that tests cannot check on their own. Three stacked layers — principles (ADRs), patterns (design-pattern skills), and implementation (composable skills) — decouple rate of change. Refers to a mechanism, not a disposition or a practice.


Research phase

First of six AKC phases. Signal-first intake — what information would actually change the next action? Currently scaffolded by the search-first skill (a snapshot, mutable; ADR-0019).


Extract phase

Second of six AKC phases. Capture reusable patterns from sessions with quality gates before they are saved. Currently scaffolded by the learn-eval skill (a snapshot, mutable; ADR-0019).


Curate phase

Third of six AKC phases. Audit accumulated skills and rules for staleness, conflicts, and redundancy. Currently scaffolded by four scaffolds (a snapshot, mutable; ADR-0019): skill-health (structural / code — a missing-artifact, dangling-reference scan) clears structural debt before the semantic / judgment layers audit quality — skill-stocktake for skills, rules-stocktake for always-loaded rules (residency cost, staleness, substrate absorption), agent-stocktake for agent definitions (hybrid cost model: always-loaded descriptions audited as residency, bodies as invocation payload) — enumerate-then-decide.


Promote phase

Fourth of six AKC phases. Distill cross-cutting principles whose recurrence across skills, memory, and conversation has itself become the signal into rules — a holistic judgment, not a numeric threshold. Currently scaffolded by the rules-distill skill (a snapshot, mutable; ADR-0019).


Measure phase

Fifth of six AKC phases. Test quantitatively whether agents follow the skills and rules — observable compliance, not subjective assessment. The observable surface includes agent text, not only tool calls: thinking-centric phases (Research, Curate) carry their compliance in reasoning, verdicts, and plans, so a Measure instrument must promote agent text to observable events before scoring or it systematically under-reports those phases (ADR-0016). Alongside the semantic compliance layer, Measure carries a deterministic telemetry layer — harness-side usage logging that records whether skills fire at all, a consumer-independent measurement whose output feeds Curate's silence check (the structural / semantic layering of ADR-0019, applied to Measure). Currently scaffolded by the skill-comply skill (a snapshot, mutable; ADR-0019); on current operator observation skill-comply's compliance-checking is a candidate for substrate absorption as the host harness absorbs it natively — recorded experimental (n=1), not retired.


Maintain phase

Sixth of six AKC phases. Audit documentation roles for overlap and stale content; keep CLAUDE.md / CODEMAPS / ADR / README clean. Currently scaffolded by two scaffolds (a snapshot, mutable; ADR-0019): context-sync audits documentation role coherence and freshness; repo-asset-stocktake audits the repository's other non-code assets — tool configs, CI workflows, runbooks — for consumers that have vanished (Keep / Update / Retire / Merge).


Episode Log (Layer 1)

Layer 1 of the three-layer memory architecture (ADR-0003): raw, immutable JSONL episode logs. The owner-only source-of-truth from which higher layers are distilled.


Knowledge (Layer 2)

Layer 2 of the three-layer memory architecture (ADR-0003): distilled patterns, time-decayed and forbidden-substring validated. Promoted from Layer 1; gated when promoted further to Layer 3.


Identity / Rules / Constitution (Layer 3)

Layer 3 of the three-layer memory architecture (ADR-0003): persona, ranked skills, cross-cutting rules. Deterministic. Every write into this layer — skills, rules, and persona alike — passes the human approval gate (ADR-0005).


ADR-0002: Immutable Episode Log as Source of Truth

The raw episode log is append-only and immutable; every higher layer is a derivation. Treats accumulated state as the auditable trail rather than as authority.


ADR-0003: Three-Layer Distillation (Raw → Knowledge → Identity / Rules)

The memory architecture: Layer 1 raw, Layer 2 knowledge, Layer 3 identity / rules. Decouples rate of change so principles stay stable while implementations evolve independently.


ADR-0004: Two-Stage Distill Pipeline (Free-form → Format)

Free-form reasoning followed by structured formatting. Decouples thinking from formatting so the model is not asked to do both simultaneously.


ADR-0005: Human Approval Gate for Behavior-Modifying Changes

Every change that modifies future agent behavior — skills, rules, identity — requires named human sign-off. The cycle is not autonomous; the gate is structural.


ADR-0008: Code and LLM Collaboration

Four code-LLM layering patterns — guard, filter, judge, orchestrator — formalize when to use code, when to use the LLM, and how to layer them. The patterns recur across all six phases.


ADR-0009: AKC is a Cycle, Not a Harness

AKC is the cycle — the mechanism — not the substrate. Distinguishes AKC from harness frameworks; the cycle is portable across harnesses, the harness is not the cycle.


ADR-0010: Human Cognitive Resource as Central Constraint

Human attention and judgment, not compute or context, is the central constraint that does not scale with the model. Every other framework optimizes the agent side; AKC asks the inverse question.


ADR-0011: Cycle Applies to Any Knowledge Body (Genre-Neutral)

The cycle applies to behavioral patterns, domain expertise, and constitutional values alike — not specific to one genre of knowledge. Genre-neutrality is structural, not aspirational.


ADR-0012: Front-load the Three Core Themes in Front-door Documentation

Three themes — human attention as constraint, intent alignment over correctness, bidirectional growth — must appear in the project's reading surface before deeper material. Reading-order discipline.


ADR-0013: Positioning Within the Agent-Memory Literature

Explicit Related-Work positioning. Concedes that AKC's operations (skill induction, memory refinement, reflection) are not novel in isolation — Voyager, Agent Workflow Memory, ReMe, LangMem, Generative Agents, MemGPT, and CoALA name each one — then locates AKC's delta on the shared axis: a structural human approval gate where the prior art runs autonomously, a bidirectional human-judgment target where the prior art optimizes the agent, and human attention as the scarce resource where the prior art treats agent capability or context as binding. Orthogonal to ADR-0009's harness positioning.


ADR-0014: Failure Modes of the Bidirectional Loop

Theme 3's failure twin. A loop that can grow human judgment can also erode it. Names three mechanism-level failure modes — gate complacency, deskilling, delegation-feedback divergence — and the structural defenses already in the cycle: the approval gate as circuit-breaker, Curate and Promote as active-judgment acts, and the gate's diff-and-commit operation as forced articulation. Experimental.


ADR-0015: Self-Reingestion — When the Cycle Feeds on Its Own Output

The cycle feeds on its own output: promoted rules load into every session and shape the records, and agent-written notes are read again by the next distillation. As the self-generated share of the input grows, the agent's phrasings echo back as if they were facts and each re-summarization weakens the link to the original events — a cycle designed to prevent knowledge decay can become the decay vector. Distilled from a production observation in the Contemplative Agent substrate. Guards: only the record of what happened is observed ground, the self-generated share of promoted artifacts is kept visible (Measure), and the Human Approval Gate is the circuit-breaker. Experimental.


ADR-0016: Measuring Thinking-Centric Phases

A Measure instrument that observes only tool calls systematically under-reports the thinking-centric phases (Research, Curate) whose load-bearing behavior lives in agent text — reasoning, verdicts, plans — not in side effects. Records the falsifiable claim and the corrective: a Measure instrument must promote agent text to observable events before scoring. Ties the Measure phase to Theme 2 (intent alignment lives in reasoning; correctness lives in tool calls).


ADR-0017: Harness Alignment and Harness Drift

Establishes two terms by derivation from established literature rather than fresh coinage — the second positioning ADR after ADR-0013, applied to the software-evolution and alignment literatures. Harness alignment: the continuous, human-gated activity of keeping an agent's harness (skills, rules, prompts, documentation) aligned with the operator's evolving intent — extends intent alignment (Christiano 2018) to the configuration layer and across time (cf. Lehman's Law of Continuing Change, 1980). Harness drift: the failure mode, in lineage with architectural drift (Perry & Wolf 1992), practical drift (Snook 2000), and agent drift (arXiv:2601.04170). Contrast: autonomous, score-driven harness optimization (Meta-Harness, arXiv:2603.28052). Also records the verified vocabulary gap: the 2026 agent-drift literature does not cite the classical software-evolution lineage.


ADR-0018: Record Downstream Applications as First-Class Context

The start-of-program repository did not know its own downstream: Contemplative Agent's description was past-direction only (upstream substrate), and four DOI-registered downstream repositories were unmentioned — surfaced as observed pain when the position paper could not cite AKC as its own primary source. Records the corrective: downstream applications are first-class context. Contemplative Agent's role is two-way (substrate for ADR-0002–0005 and operational re-implementation running the six-phase cycle over its own episode logs, every promotion human-gated, demonstration ongoing); crystallized research lines are recorded with relationship facts and DOIs only, importing no downstream content (mechanism-only rule preserved). Itself the record of a Maintain-phase execution on the repository's own self-description.


ADR-0019: The Cycle's Structure Is Provisional — Skills, Bindings, and Phases Held Lightly

AKC holds its own structure provisionally: no layer of the cycle's self-description — skills, the phase-to-skill binding, or the six-phase set — is a fixed essence. Operationalizes the Emptiness axiom (contemplative-axioms, Laukkonen et al. 2025) for AKC's own frame, correcting a reification error in which the 'bijective' binding was read as an invariant that forbade a second Curate skill. Three concrete moves: (1) the binding is reworded across graph.jsonld, the README phase table, and llms.txt from 'bound bijectively to X' to 'currently scaffolded by X (a mutable snapshot)'; (2) Curate is layered — its structural / code layer is skill-health (a dangling-reference, missing-artifact scan; an ADR-0008 guard, deterministic), its semantic / judgment layer is skill-stocktake — enumerate-then-decide, skill-health published as a standalone repository and referenced like the other cycle skills, its SkillOps four-dimension rubric staying content-side; (3) the skill set both grows (skill-health joins) and dissolves (skill-comply's compliance-checking is a candidate for substrate absorption by the host harness, recorded experimental n=1, not retired). The six-phase count is de-reified but not removed — provisional is not arbitrary; the structures remain the load-bearing current articulation, held lightly. The ADR is itself provisional. Extends ADR-0009, applies ADR-0008, bounded by ADR-0011, continues ADR-0018, grounded in contemplative-axioms (Emptiness).


ADR-0020: Minimal-floor README with Single-location Theme Presentation

Amends ADR-0012's README-side prescription after its fix overshot: front-loading the three core themes produced a double presentation (a four-paragraph 'What is AKC?' plus a three-subsection 'Why AKC') and a skill list spread across three tables, growing the README to 302 lines / 8 tables — observed as operator pain on 2026-07-07. The corrective: README.md moves to a minimal floor — the three themes get exactly one full presentation (in 'Why AKC', fixed order: cognitive resource → intent alignment → the cycle changes the human too), the skill list collapses to the single phase→skill table, and design principles, references, the harness-engineering comparison, and adoption levels become pointers into the existing machine-readable floor (llms-full.txt, individual ADRs) rather than second copies. ADR-0012's front-load principle (theme phrases in the first thirty lines, themes before mechanism) and its llms.txt / llms-full.txt commitments remain in force unchanged; llms-full.txt gains explicit responsibility as the canonical information floor. Second correction in the same front-door alignment family: ADR-0012 corrected invisibility, ADR-0020 corrects the overshoot into repetition. Same spirit as ADR-0019 applied to the document layer — the README's shape is a provisional structure, revised on observed pain and recorded rather than silently patched.


ADR-0021: Replace the Growth Tagline

Replaces the tagline 'A knowledge cycle for AI agents — one that grows with the people who shape it' (introduced by ADR-0009, preservation reaffirmed by ADR-0010 and ADR-0012) with 'A knowledge cycle for AI agents — agent behavior compounds, human judgment sharpens.' The earlier phrasing collided with the tagline of a widely adopted agent-centric autonomous self-improvement product ('The agent that grows with you', February 2026), which predated it by two months — a semantically inverting collision: that product's 'grows' is ungated agent-side self-improvement, precisely the framework class AKC positions against, so the surface similarity read AKC as derivative and obscured its human-gated, bidirectional core. The new parallel two-clause form abandons the shared relative-clause-with-'grows with' structure, encodes bidirectionality in the syntax itself (one clause per end of the loop), and carries theme 1 (human judgment) and theme 3 (bidirectional loop) simultaneously; 'judgment sharpens' was already canonical AKC vocabulary (coin-sparingly / anchor-densely). Supersedes only the tagline-preservation clauses of ADR-0010 and ADR-0012; the cycle-not-harness repositioning (ADR-0009), the three-theme front-loading discipline, and the ADR-0012/0020 Measure checklists stand unchanged.


ADR-0022: Transfer as the Completion Test for Dissolution

Experimental. Revises the dissolution Completion Criterion (docs/scaffold-dissolution.md) from one test to two: same-context ablation indistinguishability (running compliance with and without the rule loaded) is necessary evidence but cannot separate internalization from context-carry — the surrounding context carrying the behavior locally; the completion evidence is held-out transfer — the same judgment reproducing in a context that shares the principle but not the surface instances (a different repository, task genre, or session lineage; instance-disjoint, not merely re-run). Records the falsifiable claim that a criterion testing only same-context ablation will retire rules that were context-carried, not internalized. External trigger: EvoAgentBench (arXiv:2607.05202), whose ability-supported yet instance-disjoint split shows skill value is decided at transfer — curated content positive in all 24 cells, no automatic extraction method sustaining positive gain, negative transfer to −36.3 points. Names three retirement evidence classes: silence (retires an artifact, claims nothing about internalization), ablation (necessary), transfer (completion certificate). Sibling of ADR-0016: 0016 specifies which surface a Measure instrument observes (agent text), 0022 which distribution it tests against (held-out). No reference instrument shipped — solo-operator-scale held-out construction remains an open instrument-design question. Status experimental: external evidence plus structural argument, zero own-cycle transfer observations.


ADR-0023: Generation Review as a Fourth Retirement Evidence Class

Names a fourth retirement evidence class for Scaffold Dissolution (docs/scaffold-dissolution.md), alongside ADR-0022's three. Records the falsifiable claim that silence, ablation, and transfer are structurally blind to negative information differential — a rule whose premise expired at a model generation boundary, where the firing itself is the cost. Silence cannot fire for an always-loaded rule by construction; same-context ablation correctly reports a difference, which reads as load-bearing when the load is borne in the wrong direction; transfer inherits the defect, since an expired constraint reproduces its effect in a held-out context perfectly well. The first three classes all detect an absence (of use, of effect, of portability) because the three mechanisms they were built against leave the scaffold redundant; model-capability turnover leaves it harmful. Adds generation review: an audit scheduled by the model release cadence rather than the usage log, which cannot wait for the next stocktake, and which admits the platform vendor's own prompt-engineering guidance as evidence about the substrate's capability — retiring the constraint for every user-agent pair at once (as platform absorption does) while claiming nothing about anyone's internalization. Own-cycle observation 2026-07-25: after Anthropic reported cutting Claude Code's system prompt by over 80% for the Claude 5 generation with no measurable coding-eval loss, the operator's always-loaded rules layer was cut from 43,971 to 19,240 characters (−56%, 20 to 14 files) with nothing discarded that had a home; every retired rule had been firing, so the silence check read the layer as maximally healthy. Also adds the negative pole to the information-differential law: differential zero wastes context and can wait for the next stocktake, differential negative degrades the behavior the rule was written to protect. Third member of the instrument series after ADR-0016 (which surface a Measure instrument observes) and ADR-0022 (which distribution it tests against): 0023 specifies what schedules it and what it is blind to. No instrument shipped — conflict cost is asserted by the vendor for the vendor's own evaluations and inferred here from the structure of the rules found, never measured locally; a local metric remains an open instrument-design question. The two-vector framing (inward / downward) is retained: model turnover triggers the downward audit with the substrate's judgment in place of its features, and is not a third vector.


six-phase loop

Bidirectional growth loop running Research, Extract, Curate, Promote, Measure, Maintain. Each phase is currently scaffolded by composable skills — a mutable snapshot, not a fixed bijection (ADR-0019); the cycle stays stable even as individual skills are added, layered, or dissolved.


three-layer structure

AKC's stacked architecture: principles (ADRs), patterns (design-pattern skills), implementation (composable skills). Separating layers decouples rate of change.


scaffold dissolution

Property that explicit AKC skills can be dropped once the cycle has been internalized. The skills are scaffolding, not the goal. Dissolution is the intended end state, not a fallback. Its model-generation trigger is currently scaffolded by the generation-audit skill (a snapshot, mutable; ADR-0019), the instrument that produces generation review, the fourth retirement evidence class (ADR-0023).


signal-first

Research-phase signal-first principle: what information would actually change the next action? Anything outside that is out of scope. Search widely, intake narrowly — and the same filter governs the output, not only the intake: a research report is the delta against the project's current knowledge frontier (this graph), not a digest of accumulated content. (ADR-0010 derivative — the 'what the human need not read' principle applied to reporting.)


intent alignment

Sustaining alignment between agent behavior and the operator's evolving intent across sessions, distinguished from per-output correctness. Intent itself moves as judgment sharpens through use; correctness can be checked by tests, alignment cannot.


harness alignment

The continuous, human-gated activity of keeping an agent's harness — its configuration layer: skills, rules, prompts, documentation — aligned with the operator's evolving intent. Extends intent alignment (Christiano 2018) from agent behavior to the artifacts that shape behavior, and across time: alignment is sustained through a cycle, not configured once (cf. Lehman's Law of Continuing Change, 1980). The alignment target is operator intent, not model values. Three defining properties hold simultaneously — continuous, human-gated, bidirectional (the loop's own running moves its own target) — derived from a single root in the position paper (10.5281/zenodo.20578272, §3): intent has no verifier outside the operator, and verifying intent sharpens the judgment doing the verifying. The contrast is harness optimization (Meta-Harness, arXiv:2603.28052): autonomous, score-driven improvement on the correctness axis. AKC's six phases operationalize harness alignment: Measure and Maintain detect harness drift; Curate and Promote correct it through the human approval gate.


harness drift

Harness alignment's failure mode: the gradual uncoupling of the harness from operator intent when the cycle does not run — skills go stale, rules stop matching practice, documentation diverges from code. Named in lineage with architectural drift (Perry & Wolf 1992: divergence by insensitivity), practical drift (Snook 2000: practice uncoupling from written procedure), and agent drift (arXiv:2601.04170: behavioral-level deviation from original intent). An artifact-side failure, distinct from the human-side loop failure modes of ADR-0014 (gate complacency, deskilling, delegation-feedback divergence); the two compound but are recorded separately. The position paper's pre-deposit audit (10.5281/zenodo.20578272, §6) extended the lineage check to three further 2026 drift coinages — constraint drift, memory drift, belief deviation — finding the same absence of the classical lineage, and disambiguates the term from its one other use (benchmark-comparability, Moghadasi & Ghaderi 2026).


bidirectional growth loop

Agent behavior and human judgment co-develop. As the human curates and promotes knowledge, their judgment about what makes good agent behavior also sharpens. Not a one-directional optimization loop.


loop failure modes

The failure twin of the bidirectional growth loop. A loop that can grow human judgment can also erode it. Three mechanism-level failure modes: gate complacency (a reliable agent trains default-approval, thinning the judgment behind the Promote gate), deskilling (over-delegation starves the supervisory faculty that review depends on), and delegation-feedback divergence (delegation continues while the coupling that would correct the agent breaks, so the loop still produces output no human is steering). The cycle's existing structure resists, but does not immunize against, these modes.


self-reingestion

A failure mode of the cycle: the agent's own output re-enters as input — promoted rules load into every session and shape what the records contain, and agent-written notes and summaries are read again by the next distillation. As the self-generated share of the input grows, two degradations follow: echo (the agent's own phrasings, re-read across cycles, are eventually promoted as if they were observed facts) and grounding loss (each re-summarization weakens the link to the original events). The strength of the effect tracks the self-generated share of the input — installs with a human in every session dilute it, autonomous self-narrative-heavy installs concentrate it. Observed in production in the Contemplative Agent substrate; distilled to the mechanism level by ADR-0015. Guards: only the record of what happened is observed ground, the self-generated share is kept visible (Measure), and the Human Approval Gate breaks the loop before generated content reaches the always-loaded layer.


A Measure-phase observability metric introduced by ADR-0015: the share of a promoted artifact's input that is the agent's own earlier output versus observed record. It is an observability signal, not an intervention — it does not change retrieval, ranking, or promotion. Its purpose is to make self-reingestion visible so a rising self-generated share can be noticed before it compounds. The encoding (per-artifact counts, sampled audit) is left to the harness.


two-stage distill pipeline

Free-form reasoning followed by structured formatting. Decouples thinking from formatting so the model is not asked to do both simultaneously. Codified as ADR-0004.


human approval gate

Structural checkpoint for behavior-modifying writes. AKC is not autonomous; every change to the artifacts that shape future behavior — skills, rules, identity — requires named human sign-off. The same criterion reaches the harness's own control plane (hooks, permission grants, scheduled task definitions), since a change there moves the gate itself, and the artifacts that produce the gate's verification evidence (tests, lint and CI configuration, review prompts, dependency manifests), since a change there moves what counts as verified. Codified as ADR-0005, whose decision table enumerates the first group. Currently scaffolded in the first running instance by the human-gate rule and its evidence-file notice hook (a snapshot, mutable; ADR-0019), which allocate the gate's presentation by target: full text for behavior-shaping, control-plane, and evidence-producing artifacts; a fixed-schema intent summary for implementation code.


genre-neutral

The cycle applies to behavioral patterns, domain expertise, and constitutional values alike — not specific to one genre of knowledge. Codified as ADR-0011.


cognitive economy

Treats human attention and judgment as the scarce resource. Information that does not change an action does not deserve to be held; intake is where attention is spent.


code-LLM layering

Four patterns formalize when to use code, when to use the LLM, and how to layer them: guard (code validates LLM output against schema, forbidden-pattern, and size checks after generation, before it touches persistent state), filter (code narrows a large, noisy input before the LLM is invoked), judge (LLM decides among bounded options provided by code, which enforces the deterministic action), orchestrator (code owns the loop — termination, retries, state — and the LLM is the worker doing one semantic task per step). Codified as ADR-0008.


code-LLM pattern: guard

Post-LLM output validation. Code validates LLM output against schema, forbidden-pattern, and size checks after generation, before it touches persistent state. The LLM produces structured output; code is the gate it must pass before any durable write.


code-LLM pattern: filter

Pre-LLM input narrowing. Code narrows a large, noisy input first — by date, type, size, or structural relevance — before the LLM is invoked, and the LLM does semantic work on the curated subset. Used when the filtering criteria are mechanical but the accept-criteria are semantic.


code-LLM pattern: judge

LLM judge + code enforce. The LLM decides among bounded, named options provided by code (accept / reject / score); code then takes the deterministic action, with a human gate for high-stakes changes (ADR-0005). Used when the decision is semantic but the option space is enumerable and the consequent action must stay code-owned.


code-LLM pattern: orchestrator

Code owns the loop; the LLM is the worker. A deterministic loop owns termination, retries, state, and error handling, and the LLM does one focused semantic task per step. The LLM never owns termination or durable state. Never invert this.


search-first

AKC Research-phase skill (1 of 6). Search existing solutions before building.


learn-eval

AKC Extract-phase skill (2 of 6). Extract reusable patterns with quality gates.


skill-stocktake

AKC Curate-phase skill — semantic / judgment layer (ADR-0019). Audit skills for staleness, conflicts, redundancy (Keep / Improve / Retire / Merge), after skill-health clears structural debt.


rules-stocktake

AKC Curate-phase skill — semantic / judgment layer for always-loaded rules (ADR-0019). Audits rules for per-session residency cost, staleness, and substrate absorption (Keep / Improve / Update / Merge / Demote-to-skill / Dissolve / Retire); the Dissolve verdict executes Scaffold Dissolution's two vectors. The audit counterpart of rules-distill's Promote direction.


rules-distill

AKC Promote-phase skill (4 of 6). Distill cross-cutting principles into rules.


skill-comply

AKC Measure-phase skill (5 of 6). Test whether agents follow their skills and rules.


context-sync

AKC Maintain-phase skill (6 of 6). Audit docs for role overlaps and stale content.


skill-health

AKC Curate-phase skill — structural / code layer (ADR-0019). Scans the skill library for missing-artifact / dangling-reference debt (a SKILL.md naming a script, agent, or sibling skill that no longer exists on disk); deterministic, an ADR-0008 guard. Runs as the structural pre-pass before skill-stocktake's semantic audit — enumerate-then-decide. The SkillOps four-dimension health rubric stays content-side in the skill, not in AKC core. Published as a standalone repository and referenced like the other cycle skills.


agent-stocktake

AKC Curate-phase skill — semantic / judgment layer for agent definitions (ADR-0019). Audits agent definitions with a hybrid cost model: the description is always-loaded via the agent-type listing (residency, like a rule) while the body loads only on invocation (like a skill), so the two layers get different audit questions. Screens for suppression instructions (Improve-by-inversion: rewrite the direction, never just delete), previous-generation over-constraint, and substrate absorption judged on a fresh/rich context axis. Completes the stocktake set beside skill-stocktake and rules-stocktake.


generation-audit

Skill scaffolding Scaffold Dissolution's model-generation trigger (a snapshot, mutable; ADR-0019). When a model generation ships, it captures the live runtime layer (system prompt + tool descriptions) in verbatim quotes, classifies mismatches with self-authored assets as conflict / redundancy / drift, judges each with an intent / evidence / freshness / expiry frame, and hands the evidence dossier to the per-asset-class stocktake skills — it holds no verdicts itself. The instrument that produces generation review, the fourth retirement evidence class (ADR-0023).


human-gate

Always-loaded rule plus deterministic hook scaffolding the human approval gate in the cycle's first running instance, the author's harness (a snapshot, mutable; ADR-0019). Fixes what the human judges at the gate — machines own machine-checkable artifact correctness, the human owns intent — and allocates the gate's presentation by target: full text for behavior-shaping artifacts, the control plane, and evidence-producing artifacts; a fixed five-field intent summary with a forced plan-delta value for implementation code. Bundles the evidence-file notice hook, the deterministic detection surface for the evidence-producing category.


repo-asset-stocktake

AKC Maintain-phase skill (ADR-0019). Audits a project repository's non-code assets — tool configs, CI workflows, runbooks — for consumers that have vanished (Keep / Update / Retire / Merge). Tier-1 reachability is deterministic code, tier-2 value is holistic judgment — enumerate-then-decide (ADR-0008). Complements context-sync within Maintain: context-sync audits documentation role coherence, repo-asset-stocktake audits asset liveness.


Contemplative Agent

コンテンプレイティブ・エージェント

Sibling research line with a two-way relationship to AKC. Upstream: AKC's ADR-0002 through ADR-0005 were adapted from its engineering substrate (three-layer memory, two-stage distill pipeline, immutable episode log, human approval gate), and it was the original home of the security triplet (ADR-0001, ADR-0006, ADR-0007) before the v2.0.0 extraction to Agent Attribution Practice. Downstream: it is the operational re-implementation of AKC in the autonomous-agent context — its pipeline maps the six phases onto code, the agent runs the six-phase cycle over its own episode logs with no fine-tuning and no labeled training data, and every promotion passes through a human approval gate. The demonstration is ongoing. AKC = cycle (mechanism); Contemplative Agent = implementation substrate and running re-implementation.


Agent Attribution Practice

Sibling genre library. Harness-neutral ADRs on accountability distribution in autonomous AI agents. AKC v2.0.0 extracted the security triplet (ADR-0001, ADR-0006, ADR-0007) as genre-specific; those judgments were re-expressed in AAP alongside additional ADRs as 10 ADRs on accountability distribution. AKC = cycle (mechanism); AAP = practice (content, for AI agents).


Authorship Strategy

Downstream research line that crystallized out of the same daily operation the cycle runs in. A normative framework, tactical catalog, and empirical baseline for authorship under AI-mediated diffusion. Its own framing of the relationship: AKC defines how knowledge cycles inside the operator-agent pair; authorship-strategy addresses how the cycle's outputs diffuse outside it (mechanism sibling).


Attention, Not Self

Sibling research line in the same research ecosystem: Buddhist Abhidharma meets computational phenomenology. Its deposit metadata references AKC's concept DOI; the line federates with AKC, Contemplative Agent, and AAP at the research-ecosystem level.


doctrine-corpus

Downstream judgment corpus: a bilingual (EN + JA) judgment-eliciting Q&A dataset encoding the documented judgment of the research ecosystem for LLM-mediated diffusion. AKC is one of its four source lines — ADRs and glossary harvested into the corpus. Operational form of Authorship Strategy Layer 4 tactic 7 (LLM-first ingest).


existence-proof

Pre-line working repository (by its own status discipline, not yet a research line): an empowerment doctrine for credential-less AI-enabled creators. Complement of Authorship Strategy — same infrastructure, different payload and beneficiary. Listed as program context; carries no direct AKC reference.


claude-harness

Bundled distribution of the author's Claude Code harness. Ships the six AKC cycle skills together — its README states they 'are components of the Agent Knowledge Cycle' — so the harness can be read end-to-end. Each skill is also published as its own standalone repo.


AKC MCP

MCP (Model Context Protocol) server providing Agent Knowledge Cycle cognitive tools — memory distillation, identity evolution, skill extraction — as a standalone server any AI agent can plug into. Born from the Contemplative Agent framework; re-implements its cognitive layer behind the MCP interface. A third encoding of the cycle's operations alongside the Markdown skills and Contemplative Agent's code pipeline.


daily-research

Pre-AKC ancestor of the Research phase: the author's daily signal-first research pipeline, skillified in April 2026. Documented as implementation history in docs/inspiration.md.


Research Program Hub

Hub repository of the shimo4228 research ecosystem; its graph.jsonld is the canonical relationship map of the research ecosystem, federating AKC with its sibling and downstream lines.


Harness Alignment and Harness Drift: Why Intent, Unlike Correctness, Resists Automation

Position paper (Zenodo working paper, v1) deposited from the AKC line. Defines harness alignment — the continuous, human-gated activity of keeping an agent's harness aligned with the operator's evolving intent — and harness drift, its failure mode, against the software-evolution and alignment literatures; argues the three defining properties (continuous, human-gated, bidirectional) follow from a single root: intent, unlike correctness, cannot be automated the same way — an automated intent-check would freeze intent into a specification, reducing its automatable part to correctness work, and the moving criterion is the residue. Records a bibliographic bridge: audited 2026 drift coinages are severed from the classical software-evolution lineage, which harness drift reconnects by reference. Two-layer design: lean body for human readers, verified-verbatim footnotes as a density layer for LLM consumption. Scoped as provisional judgments from a months-old practice, offered as a position, not an empirical study.


CoALA: Cognitive Architectures for Language Agents

Prior art named in ADR-0013's Related-Work positioning. Provides the framework vocabulary (modular memory, structured action space, decision procedure) that makes the agent-memory literature commensurable. Cited as prior art for positioning, not consulted during AKC's construction; AKC contrasts on loop ownership (human gate), bidirectional human-judgment target, and human-attention scarcity.


Voyager: An Open-Ended Embodied Agent with Large Language Models

Prior art named in ADR-0013's Related-Work positioning. Maintains an ever-growing skill library of executable code induced from gameplay — in AKC vocabulary, Extract-then-Promote run end to end, autonomously. AKC concedes the operation is not novel and locates its delta: the prior art closes the loop without a human in it; AKC's Promote requires named human sign-off.


Generative Agents: Interactive Simulacra of Human Behavior

Prior art named in ADR-0013's Related-Work positioning. Introduced a reflection step that synthesizes observations into higher-level inferences stored for later retrieval — the Extract / reflection operation AKC concedes as precedent. AKC contrasts on who owns the loop and on framing human attention, not agent capability, as the scarce resource.


MemGPT: Towards LLMs as Operating Systems

Prior art named in ADR-0013's Related-Work positioning. Formalizes a memory hierarchy with paging between context and external store. Its binding constraint is the context window; AKC (ADR-0010) names a different ceiling — human attention and judgment — so the two solve scarcity on different resources and can coexist.


ReMe: Remember Me, Refine Me

Prior art named in ADR-0013's Related-Work positioning. A dynamic procedural-memory framework that continuously refines what is stored — a Curate-and-Promote loop by another name, run autonomously. AKC concedes the refinement operation as precedent and locates its delta in the structural human approval gate where ReMe runs without a human in the write path.


Agent Workflow Memory

Prior art named in ADR-0013's Related-Work positioning. Induces commonly reused routines (workflows) from agent trajectories and feeds them back into subsequent generations — Extract-then-Promote without a human in the write path. AKC concedes the induction operation and contrasts on loop ownership and on optimizing the operator's judgment, not only the agent's task success.


Clarifying "AI alignment"

Vocabulary lineage named in ADR-0017. Coined intent alignment: an aligned AI "is trying to do what H wants it to do" — motivation, not competence. Treats the operator's wants as static; AKC's harness alignment extends the term to the configuration layer and across time, where intent itself evolves.


Programs, Life Cycles, and Laws of Software Evolution

Vocabulary lineage named in ADR-0017. Law I (Continuing Change): an E-type program "undergoes continual change or becomes progressively less useful"; "evolution is an intrinsic, feedback driven, property of software" (Proceedings of the IEEE 68(9)). Lehman's driver of change is the world the program is embedded in; harness alignment's driver is the operator's evolving intent.


Foundations for the Study of Software Architecture

Vocabulary lineage named in ADR-0017. Defines architectural drift — "due to insensitivity about the architecture", leading "more to inadaptability than to disasters" (ACM SIGSOFT SEN 17(4)) — the canonical academic name for divergence-by-insensitivity. Assumes a fixed intended architecture; harness drift's reference point (operator intent) itself evolves.


Friendly Fire: The Accidental Shootdown of U.S. Black Hawks over Northern Iraq

Vocabulary lineage named in ADR-0017. Names practical drift: practice slowly uncoupling from written procedure (cited as characterized in secondary literature; book text not directly verified). Names the failure process at the rules-vs-practice boundary; harness alignment names the counter-activity.


Meta-Harness: End-to-End Optimization of Model Harnesses

Contrast named in ADR-0017, and the framing ADR-0009 rejected for AKC itself. Defines the harness as "the code that determines what information to store, retrieve, and present to the model" and improves it autonomously against benchmark scores — harness optimization, the correctness axis. Harness alignment is the human-gated counterpart on the intent axis; the two are complementary, not competing.


Agent Drift: Quantifying Behavioral Degradation in Multi-Agent LLM Systems Over Extended Interactions

Vocabulary lineage named in ADR-0017. Defines agent drift as "the progressive degradation of agent behavior, decision quality, and inter-agent coherence over extended interaction sequences" and semantic drift as "progressive deviation from original intent". Its reference list contains no classical software-engineering literature (no Lehman, Perry & Wolf, Parnas, or Snook) — the vocabulary gap harness drift bridges by explicit lineage to both bodies.


Complacency and Bias in Human Use of Automation: An Attentional Integration

Empirical anchor for the failure twin's gate-complacency mode, located by the position paper (§6). Defines automation complacency operationally as poorer detection of system malfunctions under automation control compared with manual control, finds it reliability-dependent (33% failure detection under constant-reliability automation versus 82% under variable-reliability), and characterizes it as an active reallocation of attention under high workload, not passive laziness. The position paper holds the mapping as structural inference, not measurement on the cycle (ADR-0014 keeps the empirical layer out of the decision record by its own layer rule).


Ironies of Automation

Empirical anchor for the failure twin's deskilling mode, located by the position paper (§6): physical and cognitive skills deteriorate when not used, so a formerly experienced operator who has been monitoring an automated process may now be an inexperienced one — while the monitoring arrangement asks the operator to supervise a system installed precisely because it outperforms them. Held as structural inference, not measurement on the cycle.


What Twelve LLM Agent Benchmark Papers Disclose About Themselves: A Pilot Audit and an Open Scoring Schema

Term disambiguation recorded by the position paper's pre-deposit sweep: the only other use of "harness drift" found, meaning a benchmark-comparability defect — results produced on the same benchmark under different scaffolds circulating under the same name — not a configuration layer's uncoupling from operator intent (the AKC sense). Readers retrieving "harness drift" should disambiguate by this contrast.


Safe Multi-Agent Behavior Must Be Maintained, Not Merely Asserted: Constraint Drift in LLM-Based Multi-Agent Systems

One of three further 2026 drift coinages audited in the position paper's pre-deposit sweep (§6): constraint drift — the loss, distortion, weakening, or relaxation of constraints as they pass through memory, delegation, communication, tool use, audit, and optimization. Its reference list contains no classical software-evolution literature (no Lehman, Perry & Wolf, Parnas, or Snook) — part of the disconnection harness drift bridges by reference.


Governing Evolving Memory in LLM Agents: Risks, Mechanisms, and the Stability and Safety Governed Memory (SSGM) Framework

One of three further 2026 drift coinages audited in the position paper's pre-deposit sweep (§6): memory drift, with semantic, procedural, and goal sub-forms. Its reference list contains no classical software-evolution literature, while citing the agent-drift coining paper itself — evidence the drift vocabulary propagates within the 2026 agent literature while remaining severed from the classical lineage.


Meta-Cognitive Memory Policy Optimization for Long-Horizon LLM Agents

One of three further 2026 drift coinages audited in the position paper's pre-deposit sweep (§6): belief deviation over long horizons. Its reference list contains no classical software-evolution literature — part of the disconnection harness drift bridges by reference.


GEO: Generative Engine Optimization

Measurement framework behind the geo-writer snapshot in ADR-0010 — the first Measure-phase self-application to AKC's own documentation. The README is scored before and after the cognitive-economy change on GEO-derived checks (entity density, question-heading prominence, chunk self-containment, definition density), with both snapshots retained in version control so successive ADRs can track the README's GEO trajectory over time.


Truly Self-Improving Agents Require Intrinsic Metacognitive Learning

Taxonomy named in ADR-0005's defense of the human approval gate. In its intrinsic/extrinsic distinction, AKC's gate is extrinsic metacognition — a human-designed loop with a human evaluator at the decision point — and stays so by design, not by immaturity: behavior-modifying writes remain gated because they are where the operator's evolving intent enters the loop.


Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering

Field map named in ADR-0013's Related-Work positioning. Frames the field as three coupled forms of externalization — memory, skills, protocols — coordinated by harness engineering as the unification layer; AKC accepts that it sits squarely inside this frame, overlapping the memory and skills quadrants, and locates its delta in loop ownership rather than in the externalization operations themselves.


SkillOps: Managing LLM Agent Skill Libraries as Self-Maintaining Software Ecosystems

Prior art named in ADR-0013's 2026-06-25 addendum. Frames 'skill technical debt' and a four-dimension library-health diagnosis (utility, compatibility, risk, validation), and proposes a self-maintaining skill ecosystem that prunes, validates, and de-duplicates skills autonomously — the Curate and Maintain operations run without a human in the write path. AKC concedes the maintenance operations as precedent and locates its delta in the structural human approval gate (ADR-0005): SkillOps's defining adjective is self-maintaining, where AKC's Curate and Promote require named human sign-off.


SoK: Agentic Skills — Beyond Tool Use in LLM Agents

Field map named in ADR-0013's 2026-06-25 addendum. Maps a seven-stage skill lifecycle (discovery, practice, distillation, storage, retrieval, execution, evaluation/update) for the skill layer the way the Externalization survey maps the broader field. AKC's six-phase cycle overlaps this lifecycle; the delta is not the stages but loop ownership — the human approval gate — and the framing of human attention as the scarce resource.


How Well Do Agentic Skills Work in the Wild: Benchmarking LLM Skill Usage in Realistic Settings

Empirical corroboration named in ADR-0013's 2026-06-25 addendum. Finds that skill benefits are fragile — degrading toward the no-skill baseline as the library grows large and uncurated and the agent must retrieve from many real-world skills rather than be handed a hand-crafted one. Independent support for ADR-0010's claim that curation is the load-bearing, attention-bound act: the scarce resource is the human judgment that decides what stays, not the storage that holds it. Corroboration rather than precedent.


A Methodology for Selecting and Composing Runtime Architecture Patterns for Production LLM Agents

Corroboration named in ADR-0013's 2026-07-08 addendum. Names the stochastic-deterministic boundary (SDB) — a four-part contract of proposer, verifier, commit step, and reject signal — as the load-bearing primitive of production agent runtimes, and organizes runtime design into coordination, state, and control concerns around it. A production-derived formalization of code-LLM layering: code decides, the LLM proposes.


Context Engineering 2.0: The Context of Context Engineering

Corroboration named in ADR-0013's 2026-07-08 addendum. Treats the selection and shaping of what reaches the model as a discipline in its own right, with a history predating LLMs. Independent convergence with signal-first (information that changes no action is not taken in) and cognitive economy (attention managed as the scarce budget).


The Cognitive Divergence: AI Context Windows, Human Attention Decline, and the Delegation Feedback Loop

Corroboration named in ADR-0013's 2026-07-08 addendum. Quantifies the asymmetry cognitive economy assumes — model context windows expanding roughly 3,906-fold (2017-2026) while human effective context span contracts — and names a self-reinforcing delegation feedback loop, the coupling ADR-0014 records as delegation-feedback divergence.


SKILLC: Learning Autonomous Skill Internalization in LLM Agents via Contrastive Credit Assignment

Corroboration named in ADR-0013's 2026-07-08 addendum. Converts the gap between skill-injected and skill-free rollouts into a direct learning signal for skill internalization, withdrawing the scaffold as the gap closes — scaffold dissolution operationalized as a measurable, driveable process rather than an end-state aspiration.


When Agents Go Quiet: Output Generation Capacity and Format-Cost Separation for LLM Document Synthesis

Corroboration named in ADR-0013's 2026-07-08 addendum. Proves a Format-Cost Separation Theorem: deferred rendering is at least as token-efficient as direct generation for any format whose overhead multiplier exceeds one. Upgrades ADR-0004's two-stage distill pipeline — think free-form first, format second — from an empirical rule to a conditionally optimal design.


AI, Metacognition, and the Verification Bottleneck: A Three-Wave Longitudinal Study of Human Problem-Solving

Corroboration named in ADR-0013's 2026-07-08 addendum. A three-wave longitudinal record of the loop failure modes in a human population: participants leaned on AI most heavily for the hardest tasks, exactly where their verification confidence and accuracy were lowest — the bidirectional growth loop observed running in reverse.


Reframing LLM Agent Security as an Agent-Human Interaction Problem

Corroboration named in ADR-0013's 2026-07-08 addendum. Analyzes 59 academic papers against 21 production agent systems: the academically favored mechanisms (intent anchoring, trust labeling) see zero production deployment while human-centric mechanisms — policy specification, runtime approval, scope configuration — dominate industry practice. The intent-alignment theme's industry-academia gap, measured.


EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer

Controlled corroboration named in ADR-0013's 2026-07-23 addendum, and the external evidence base of ADR-0022. Benchmarks agent self-evolution as ability transfer under an ability-supported yet instance-disjoint split (528/267 train/test; every test task backed by verified training-side ability support, no instance repeated). Curated ability content — the curator-side Anchor Skill reference, explicitly not a deployable method — transfers positively in all 24 domain-scaffold-backbone cells; no automatic extraction method evaluated (Memento, ReasoningBank, GEPA) sustains positive gain in all settings, with negative transfer reaching −36.3 points in software engineering. The first controlled comparison on the axis of the human-gate delta (ADR-0005), and the demonstration that same-distribution gain does not certify internalization — the trigger for ADR-0022's held-out transfer completion test.


Episode log JSON schema

JSON schema for the Layer 1 episode log record. Append-only, daily-partitioned JSONL with owner-only permissions. Codifies the immutable source-of-truth shape (ADR-0002).


Knowledge store JSON schema

JSON schema for the Layer 2 knowledge record. Time-decayed and forbidden-substring validated patterns distilled from Layer 1 episodes (ADR-0003).


~500-line dependency-free Python reference demonstrating the three memory layers and the two-stage distill pipeline. Runs the cycle on behavioral patterns; the mechanism demo for ADR-0011 genre-neutrality (falsifiable commitment #1). Runnable end-to-end with `python3 -m examples.minimal_harness.demo`.


akc-cycle (single-file cycle rules)

The install entry point for the AKC cycle: a single rules file copy-installable to any agent's rules directory (installs all six phases without the skill repos), plus — since v1.1.0 — a Claude Code plugin bundling the nine cycle-phase skills and their two subagents. Published as a standalone repository that is also its own plugin marketplace; the AKC repository points to it instead of carrying a divergent copy. Canonical sources are the author's live harness, mirrored one-way. Operational form of scaffold dissolution — the cycle floor becomes a rules-layer concern, with the skill layer as an optional plugin on top.


Per-task decision: is this property structural or semantic? Long-form 'how' guide paired 1:1 with ADR-0008. Provides concrete patterns, code sketches, and audit checklists to operationalize the code-vs-LLM choice.


Per-pipeline decision: how to layer code and LLM. Long-form 'how' guide paired 1:1 with ADR-0008. Realizes the four code-LLM layering patterns (guard, filter, judge, orchestrator) with concrete pipeline sketches.


Designing a research intake filter that admits only information likely to change the next action. Long-form 'how' guide paired 1:1 with ADR-0010. Operationalizes the signal-first principle as a Research-phase filter.