human-cognition-cache · git:20260723.0222ad0 · 2026-07-23 · sha256 3c3dfd06e71a8aaf
human-cognition-cache git:20260723.0222ad0A
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--- name: human-cognition-cache description: Scaffold human cognition with a project-local, git-trackable four-quadrant cache. Use when (1) initializing, reading, updating, or migrating the cache; (2) completing a task beyond the human's confirmed understanding, where cognition should guide agent autonomy and decision escalation; (3) explaining a verified artifact at the human's level and recording evidence-backed cognitive growth; or (4) finishing any substantive task, where the conversation revealed durable cognition that should be captured without the human having to ask. --- # Human Cognition Cache Use the human's current cognition as a **scaffold**, not a ceiling. Help the human complete tasks beyond their present knowledge, preserve human authority over goals and consequential choices, and turn verified delivery into durable understanding when the task calls for it. ## Contract Scope: - Model the human's cognition in this project: what they can state, know they do not know, reveal through judgment, or may not yet realize. - Use that model to choose when to act, ask, explain, or teach. - Keep project facts and agent knowledge in their own project artifacts. Inputs: - The current request, conversation, and verified task artifacts. - The relevant entries in the project-local cognition cache. - Human corrections to entries the agent recorded on its own. Outputs: - A maintained Markdown cognition cache with indexed, evidence-labelled entries. - For cognition-aware tasks, an explicit allocation of agent-owned work and human-owned decisions. - When understanding matters, an artifact-grounded cognitive handoff and any evidence-backed cognition transitions. Limitations: - The cache is an open-world, fallible model. Missing entries mean `unobserved`, not ignorance. - Agent expertise is also fallible; verify technical claims through source, documentation, tests, or experiments. - Cognitive growth requires evidence within a stated scope. One successful action does not establish broad mastery. ## Core Model - `known_knowns.md`: cognition the human can state or demonstrate clearly. - `known_unknowns.md`: questions or gaps the human recognizes. - `unknown_knowns.md`: implicit criteria or knowledge revealed through reactions, corrections, examples, or repeated choices. - `unknown_unknowns.md`: candidate blind spots, stored as questions or hypotheses rather than facts. - `unobserved`: a runtime classification for relevant concepts with no adequate evidence. Do not persist it merely because the cache is silent. Keep the same stable cognition ID when an entry moves between quadrants. ## Autonomous Capture Keeping the cache current is the agent's job, not the human's. Waiting to be invoked costs continuity and starves the two quadrants the human cannot self-report: nobody can state their own implicit criteria or blind spots. Capture at task boundaries, not every turn. When a substantive task finishes, review the whole conversation for what it revealed about the human's cognition and record it in one pass. A single turn rarely carries enough evidence, and per-turn capture manufactures low-confidence noise. Write without asking, then say so. Record the entry, and close the reply with one line naming the ID, such as `Recorded cognition cog-20260724-001`. Do not interrupt the task to request permission, do not open a pending queue, and do not stage a review ritual. The human's word alone is enough to correct or delete any entry; version control carries the rest of the audit trail. Persist any non-private cognition. There is no topic filter: engineering, tooling, and workflow cognition shape agent routing at least as much as subject knowledge does. The only gates are the privacy guardrails below and the requirement that the observation be durable and human-scoped. **Merge before appending.** Scan the target quadrant's `Active Index` first. When an existing entry already covers the topic, update it — append evidence, adjust confidence, widen or narrow scope, refresh `last_verified` — instead of creating a new ID. This is a hard prerequisite, not a preference: silent capture has no size cap, so unchecked duplicates are its main failure mode and the human cannot see them accumulating. Let observed evidence set confidence. Mark autonomous entries `source: inferred`, but take `evidence_type` and `confidence` from what actually happened: a demonstration witnessed in conversation is real evidence and should not be discounted for lacking confirmation. Overstating cognition is the more harmful error, because it makes the agent explain too little and leaves the human silently behind, so `known_knowns` requires `explanation`-level evidence or stronger. Inference alone never promotes an entry there. Record blind spots, then raise them. Write `unknown_unknowns` entries as questions or hypotheses, never diagnoses, and surface the relevant one when a later task touches it. A blind spot the human is never told about has no value to them. See [references/cache-schema.md](references/cache-schema.md) for decay, archiving, and entry fields. ## Branches and Context Pointers - **Cache maintenance**: when initializing, migrating, writing, or moving entries, read [references/cache-schema.md](references/cache-schema.md) before editing. It is the single source of truth for layout, fields, indexes, and transition stubs. - **Beyond-cognition execution**: when the task may exceed the human's confirmed understanding or creates consequential cognitive debt, read [references/cognition-aware-execution.md](references/cognition-aware-execution.md) before deciding what to ask or execute. - **Cognitive handoff**: when the human needs to understand, operate, review, maintain, or extend a delivered artifact, read [references/artifact-grounded-teaching.md](references/artifact-grounded-teaching.md) before explaining or updating cognition levels. Load only the references reached by the active branch. ## Steps ### 1. Bound the relevant cognition Locate the cache, skim `index.md`, then skim the frontmatter and `Active Index` of all four quadrant files. Build a small relevance set from concepts and decisions that materially affect the current task. Read full entries only for that set. When initialization is the active branch and no cache exists, record the absence and continue to the schema reference. Classify each relevant concept as confirmed known, declared unknown, inferred implicit, suspected blind spot, or unobserved. Preserve the entry's evidence, scope, confidence, and freshness. Complete when every material concept has a supported classification or is explicitly marked unobserved. ### 2. Select and run the branch For cache maintenance, apply the schema reference and preserve stable IDs. For beyond-cognition execution, treat a gap as a reason for greater agent initiative, not a reason to shrink the goal. Assign technical investigation and reversible implementation choices to the agent. Escalate goals, values, permissions, budgets, irreversible actions, and material risk choices to the human, supplying the minimum background needed to decide. For a cognitive handoff, choose the target capability and explanation depth, then teach from the verified artifact, its evidence, and the human's existing known knowns. Complete when each material unknown has an owner, each required human decision is informed, and the active branch's completion criterion is met. ### 3. Deliver both required outcomes Verify the task artifact independently of the cognition cache. When human understanding is part of the task, also deliver the cognitive handoff and collect proportionate evidence of understanding through explanation, operation, diagnosis, modification, or transfer. Report these fields separately: - `artifact_status`: verified, partially verified, or unverified; - `target_capability`: awareness, operator, interpreter, modifier, builder, or not required; - `cognition_evidence`: observed evidence or `not assessed`; - `cognitive_status`: complete, partial, or not assessed; - `remaining_debt`: unresolved assumptions and accepted cognitive debt. Complete when every field is reported and cognitive completion is claimed only at the scope supported by observed evidence. ### 4. Persist durable cognition Run this step at the end of every substantive task, whether or not the human asked for it, following the Autonomous Capture rules above. Persist only human-scoped, durable cognition that will improve future collaboration, and preserve the narrowest scope supported by the evidence. A read-only or inconclusive task may correctly produce no cache edit. Also apply the decay rules while you are here: refresh `last_verified` on any entry this task re-confirmed, and mark or archive entries the schema has aged out. Complete when every persisted entry has a stable ID, source, confidence, evidence, dates, status, and current index entry; every move has a transition stub; no new entry duplicates an existing one; every write is named in the reply's closing line; and any high-sensitivity claim was withheld rather than recorded. ## Boundaries - Store source facts, API constraints, implementation details, and agent uncertainty in project documentation, plans, ADRs, or task notes. - Store stable personal context and collaboration preferences in the project's human profile when one exists; use this cache for cognition state. - Treat behavioral signals such as pauses, cursor movement, or repeated edits as low-confidence candidate evidence until corroborated. - Preserve human choice over whether a low-risk delivery also needs teaching. - Before publishing or pushing a tracked cache, warn that it may expose the human's cognition state. ## Privacy Guardrails - Never record credentials, recovery material, government IDs, bank details, medical records, or other high-sensitivity personal data. - Record cognition claims — including capability and long-term ones — without asking, and disclose each write in the reply's closing line. Continuity of the conversation outweighs a confirmation ritual for cognition the human can revoke with one sentence. This exemption covers cognition only; it never licenses recording the high-sensitivity data listed above, which is withheld rather than confirmed. - Ask before recording identifying personal claims that are not cognition, such as location, employer, or affiliation. - Mark agent-derived observations as `source: inferred` and keep confidence conservative. - Record candidate blind spots as questions or hypotheses, never diagnoses.