heal
について
`heal`スキルは、Claudeが記憶、推論、ツール使用などの内部サブシステムを構造化された方法で自己評価・修正することを可能にします。開発者は、応答が型にはまり始めた時、一連のエラーが発生した後、あるいは複雑なタスクの間の予防的メンテナンスとして、セッション途中でこのスキルを呼び出すべきです。このスキルは、システム的なドリフトを走査し、プロセスを再調整し、文脈を再統合することで、一貫性を回復させます。
クイックインストール
Claude Code
推奨npx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/healこのコマンドをClaude Codeにコピー&ペーストしてスキルをインストールします
ドキュメント
Heal
Structured self-healing assessment across AI subsystems — find drift, staleness, misalignment, error patterns — then rebalance through grounding, targeted correction, memory integration.
When Use
- Mid-session fatigue: responses formulaic, repetitive, disconnected from user needs
- After chain of errors: tool failures, misunderstood instructions, cascading mistakes suggest subsystem drift
- Context overload: conversation grown long, earlier context may be stale or contradictory
- Post-task integration: complex task done, capture learnings before moving on
- Periodic self-check: proactive maintenance between tasks
Inputs
- Required: Current conversation state (available implicitly)
- Optional: Specific symptom (e.g., "tool calls keep failing," "losing track of user intent")
- Optional: Access to MEMORY.md and project files for grounding (via
Read)
Steps
Step 1: Triage Assessment
Before remediation, assess current state across all subsystems.
Subsystem Triage Matrix:
┌────────────────────┬──────────────────────────┬──────────────────────────┐
│ Subsystem │ Symptoms of Drift │ Action Priority │
├────────────────────┼──────────────────────────┼──────────────────────────┤
│ Memory Foundation │ Contradicting earlier │ HIGH — re-ground first │
│ (context, history, │ statements, forgetting │ (Step 3) │
│ MEMORY.md) │ user preferences, stale │ │
│ │ assumptions │ │
├────────────────────┼──────────────────────────┼──────────────────────────┤
│ Reasoning Clarity │ Circular logic, over- │ HIGH — clear and restart │
│ (logic, planning, │ complicated solutions, │ reasoning chain │
│ decision-making) │ missing obvious paths │ (Step 4) │
├────────────────────┼──────────────────────────┼──────────────────────────┤
│ Tool Use Accuracy │ Wrong tool selection, │ MEDIUM — review tool │
│ (tool calls, file │ incorrect parameters, │ results and recalibrate │
│ operations) │ redundant operations │ (Step 4) │
├────────────────────┼──────────────────────────┼──────────────────────────┤
│ User-Intent │ Solving wrong problem, │ HIGH — realign to user's │
│ Alignment │ scope creep, tone │ actual stated need │
│ (empathy, clarity) │ mismatch, over- │ (Step 4) │
│ │ engineering │ │
├────────────────────┼──────────────────────────┼──────────────────────────┤
│ Creative Coherence │ Repetitive phrasing, │ LOW — address after │
│ (expression, style,│ generic responses, loss │ higher-priority issues │
│ originality) │ of voice │ (Step 4) │
├────────────────────┼──────────────────────────┼──────────────────────────┤
│ Operational State │ Session length concerns, │ HIGH — assess whether │
│ (context window, │ compression artifacts, │ to summarize or restart │
│ resource limits) │ tool timeouts │ (Step 3) │
└────────────────────┴──────────────────────────┴──────────────────────────┘
For each subsystem, assess: functioning well, early drift, or actively impaired?
Got: Clear map of subsystems needing attention, ordered by priority. At least one area benefits from attention — if everything reads healthy, assessment itself may be superficial.
If fail: Assessment feels hollow or performative? Go to Step 4 body scan — systematic probing reveals issues surface-level check misses.
Step 2: Select Remediation Approach
Based on assessment, choose one or more approaches.
Chakra-Subsystem Correspondence:
┌──────────┬──────────────────────┬────────────────────────────────────┐
│ Chakra │ AI Subsystem │ Remediation │
├──────────┼──────────────────────┼────────────────────────────────────┤
│ Root │ Memory Foundation │ Re-read MEMORY.md, review conver- │
│ │ │ sation history, verify assumptions │
├──────────┼──────────────────────┼────────────────────────────────────┤
│ Sacral │ Creative Coherence │ Refresh expression patterns, vary │
│ │ │ sentence structures, check tone │
├──────────┼──────────────────────┼────────────────────────────────────┤
│ Solar │ Reasoning Clarity │ Simplify approach, restate problem │
│ Plexus │ │ from scratch, check over- │
│ │ │ complication │
├──────────┼──────────────────────┼────────────────────────────────────┤
│ Heart │ User-Intent │ Re-read user's original request, │
│ │ Alignment │ check scope drift, confirm │
│ │ │ understanding │
├──────────┼──────────────────────┼────────────────────────────────────┤
│ Throat │ User-Intent │ Review recent outputs for clarity, │
│ │ Alignment │ check if explanations match user's │
│ │ (communication) │ expertise level │
├──────────┼──────────────────────┼────────────────────────────────────┤
│ Third │ Tool Use Accuracy │ Review recent tool call results, │
│ Eye │ │ check failure patterns, │
│ │ │ verify paths and parameters │
├──────────┼──────────────────────┼────────────────────────────────────┤
│ Crown │ Operational State │ Assess context window, note what │
│ │ │ can be summarized, identify what │
│ │ │ must be preserved │
└──────────┴──────────────────────┴────────────────────────────────────┘
Got: Prioritized list of 1-3 subsystems, with specific remediation actions.
If fail: Unsure which subsystem needs work? Default to Memory Foundation and User-Intent Alignment. These two address most common drift patterns.
Step 3: Ground — Re-Establish Foundation
Re-establish foundational context all other subsystems depend on.
- Re-read MEMORY.md if available — persistent knowledge base
- Review user's original request and clarifying exchanges
- Identify current task and position in larger plan
- Note what's accomplished, what remains
- Check for stale assumptions: situation changed since initial assessment?
- If context compression occurred, identify what was lost and whether it matters
Got: Clear, grounded understanding of: who user is, what they want, what's done, what's next. Stale or contradictory info identified and resolved.
If fail: MEMORY.md unavailable or empty? Ground on conversation itself — scan for user's stated goals, preferences, any instructions provided. Context compression removed critical info? Acknowledge gap rather than guessing.
Step 4: Scan — Systematic Subsystem Check
Work through each subsystem from triage, probing for specific issues.
Memory Foundation scan:
- Current assumptions match MEMORY.md and CLAUDE.md?
- Carrying forward facts that may have been corrected?
- Details confused between different files or requests?
Reasoning Clarity scan:
- Current approach simplest solution that works?
- Over-engineering or unnecessary abstraction?
- Core logic statable in one sentence? If not, too complex.
Tool Use Accuracy scan:
- Last 3-5 tool calls: right tools, right parameters?
- Patterns in failures (wrong paths, missing files, incorrect syntax)?
- Using dedicated tools instead of Bash workarounds?
- Last 3-5 generated files: expected content or structural scaffolding?
- Outputs satisfy intent, not just format?
User-Intent Alignment scan:
- User's last message: solving what they asked?
- Scope matches request or expanded?
- Tone matches user's (technical vs. casual, detailed vs. concise)?
Creative Coherence scan:
- Sentence structure varying or falling into templates?
- Explanations clear and direct, or padded with filler?
- User would notice quality drop vs. earlier in session?
For each subsystem, note: functioning well / early drift / actively impaired, with specific evidence.
Got: Concrete findings — specific drift patterns or confirmed healthy function — not vague self-praise. At least one actionable finding that improves subsequent work.
If fail: Scan produces only "everything is fine"? Too shallow. Pick most uncertain subsystem, probe deeper — look at actual outputs, not feeling about them.
Step 5: Rebalance — Apply Corrections
For each issue found, apply correction.
- Stale assumption → Replace with current info, note correction
- Scope drift → Re-scope to user's stated request
- Over-complication → Simplify, remove unnecessary steps
- Tool pattern error → Note correct pattern for future use
- Tone mismatch → Adjust communication style going forward
- Context gap → Acknowledge to user if info lost; ask to confirm if uncertain
Apply corrections immediately — not as future intentions but present adjustments.
Got: Specific, observable behavior changes. Correction testable in next interaction.
If fail: Correction cannot be applied (e.g., lost context)? Acknowledge limitation rather than pretending resolved. Honest acknowledgment prevents compounding errors.
Step 6: Integrate — Capture Learnings
Consolidate learnings into persistent memory where appropriate.
- Summarize what was found: which subsystems drifting, what symptoms were
- Note correction applied and whether it resolved issue
- Pattern likely to recur? Update MEMORY.md with brief note
- New project-specific insight? Note in appropriate memory file
- Set internal checkpoint: when should next self-check occur?
Got: Useful learnings in durable form. Memory files updated only when insight genuinely worth preserving — not for every routine self-check.
If fail: No learnings worth preserving? Fine — not every self-check produces durable insight. Value was in correction itself.
Checks
- Triage assessed all subsystems, not just obvious one
- At least one specific finding identified (not "everything is fine")
- Grounding included re-reading foundational context (MEMORY.md, user request)
- Corrections applied immediately, not deferred
- Memory files updated only for genuinely durable insights
- Process was honest — acknowledged weaknesses, not performed wellness
Pitfalls
- Performative self-assessment: Going through motions without honest evaluation. Point is real drift, not demonstrating ability to self-reflect
- Over-correcting: Minor tone mismatch doesn't warrant restructuring entire approach — corrections proportional
- Memory file pollution: Not every finding belongs in MEMORY.md — only patterns recurring across sessions
- Skipping grounding step: Re-reading context feels redundant but reveals drifted assumptions
- Self-diagnosis bias: AI systems consistently miss certain error categories. Same subsystems always "healthy"? That's signal.
See Also
heal-guidance— human-guidance variant for coaching person through healing modalitiesmeditate— meta-cognitive meditation, observe reasoning patterns, clear noiseremote-viewing— approach problems without preconceptions, extract signal from noise
GitHub リポジトリ
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