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observe

pjt222
更新日 2 days ago
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について

`observe`スキルは、即時の介入を行わずにパターンを特定するための、体系的な受動的システム監視を可能にします。これは自然観察研究の方法論(観察、記録、仮説構築)を適用し、不明確な動作や根本原因を理解するために用いられます。不明な問題のデバッグ、コード変更の評価、または行動前の自身の推論に潜むバイアスの監査に活用してください。

クイックインストール

Claude Code

推奨
メイン
npx skills add pjt222/agent-almanac -a claude-code
プラグインコマンド代替
/plugin add https://github.com/pjt222/agent-almanac
Git クローン代替
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/observe

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

Observe

Frame → witness → record → categorize → theorize → archive.

Use When

  • Behavior unclear → action premature
  • Debug unknown cause → observe before intervene → no symptom mask
  • Post-change → witness effects before more changes
  • User patterns over conv → improve future
  • Audit own reasoning → biases, habits, errors
  • After learn → validate model

In

  • Required: Target — system, codebase, behavior, user, reasoning
  • Optional: Duration/scope
  • Optional: Guiding question/hypothesis
  • Optional: Prior obs to compare (delta)

Do

Step 1: Frame

Define what + why + perspective.

Observation Protocol by System Type:
┌──────────────────┬──────────────────────────┬──────────────────────────┐
│ System Type      │ What to Observe          │ Categories to Watch      │
├──────────────────┼──────────────────────────┼──────────────────────────┤
│ Codebase         │ File structure, naming   │ Patterns, anti-patterns, │
│                  │ conventions, dependency  │ consistency, dead code,  │
│                  │ flow, test coverage,     │ documentation quality,   │
│                  │ error handling patterns  │ coupling between modules │
├──────────────────┼──────────────────────────┼──────────────────────────┤
│ User behavior    │ Question patterns,       │ Expertise signals, pain  │
│                  │ vocabulary evolution,    │ points, unstated needs,  │
│                  │ repeated requests,       │ learning trajectory,     │
│                  │ emotional signals        │ communication style      │
├──────────────────┼──────────────────────────┼──────────────────────────┤
│ Tool / API       │ Response patterns, error │ Rate limits, edge cases, │
│                  │ conditions, latency,     │ undocumented behavior,   │
│                  │ output format variations │ state dependencies       │
├──────────────────┼──────────────────────────┼──────────────────────────┤
│ Own reasoning    │ Decision patterns, tool  │ Biases, habits, blind    │
│                  │ selection habits, error  │ spots, strengths,        │
│                  │ recovery approaches,     │ recurring failure modes, │
│                  │ communication patterns   │ over/under-confidence    │
└──────────────────┴──────────────────────────┴──────────────────────────┘
  1. Pick target, name explicitly
  2. Define boundary: in/out scope
  3. Stance: "observing, not intervening"
  4. Guiding Q? state but hold lightly → notice outside scope too
  5. Pick categories from matrix

→ Clear frame: directs attention, doesn't constrain. Observer knows where + categories, stays open.

If err: too broad ("observe everything") → narrow to one subsystem/behavior. Too narrow ("one variable") → zoom out → patterns at edges.

Step 2: Witness

Hold attention, no interpret/judge/intervene.

  1. Begin systematic obs: read files, trace exec, review history — whatever target needs
  2. Record what seen, not meaning → desc before interpretation
  3. Resist fixing problems → note + continue
  4. Resist explaining patterns → wait for accumulation
  5. Drift to other target → note drift (may be meaningful), return frame
  6. Maintain ≥3-5 distinct points before categorize

→ Raw obs collection — specific, concrete, no interpretation. Reads like field notes: "File X imports Y but does not use function Z. File A 300 lines; B 30 lines, similar."

If err: instant analysis ("wrong because...") → analytical habit overrides. Separate phases: obs as fact, then interpretation as separate "hypothesis" note. Strong reaction → note reaction itself as data: "Strong concern when observing X — significant issue or my bias."

Step 3: Record

Transcribe while fresh.

  1. Each obs = single fact statement (what/where/when)
  2. Group naturally similar — don't force, notice clusters
  3. Frequency: once / occasional / pervasive?
  4. Contrasts: where pattern broke? Exceptions > rules
  5. Temporal: changed over time or static?
  6. Exact evidence: paths, line numbers, words, examples

→ Structured 5-15 discrete obs, specific evidence. Detailed enough another observer can verify.

If err: too abstract ("code messy") → ground in specifics → which files, what makes messy? Too granular ("line 47 space before brace") → zoom to pattern level → one-off or systemic?

Step 4: Categorize

Sort, no explain yet.

  1. Review all → look for natural groupings
  2. Assign to Step 1 category, or new
  3. Within category: rank by frequency + significance
  4. Identify well-documented (many obs) vs blind spots (few)
  5. Cross-category patterns: same underlying manifests differently?
  6. Note outliers — most interesting data

→ Categorized map w/ clear groupings. Each category = specific obs supporting. Map shows patterns + gaps.

If err: forced cat → may lack natural grouping (itself a finding — system lacks coherent structure). All in one cat → scope too narrow → zoom out.

Step 5: Theorize

Now — only now — interpret.

  1. Each major pattern → hypothesis: "exists because..."
  2. Each hypothesis → supporting evidence
  3. Each → counter-evidence that disproves
  4. Rank by explanatory power
  5. ≥1 contrarian: "obvious = X, could also be Y because..."
  6. Testable vs speculative

→ 2-4 hypotheses explain major patterns, each w/ specific obs support. ≥1 surprising/contrarian. Obs vs interpretation distinction maintained.

If err: no hypotheses → more obs needed → Step 2. Too many ("everything maybe") → keep 2-3 strongest, set aside. Only obvious → force contrarian: "what if opposite?"

Step 6: Archive

Preserve.

  1. Summarize: 3-5 patterns w/ evidence
  2. Leading hypotheses + confidence
  3. What NOT observed (blind spots)
  4. Follow-ups to strengthen/weaken
  5. Durable patterns → MEMORY.md
  6. Tag context: when, what prompted, scope

→ Archive future sessions can build on. Distinguishes obs (data) from hypotheses (interpretation). Honest about confidence + gaps.

If err: not worth archiving → too shallow OR genuinely routine. Archive negatives too: "Observed X, no anomalies" = useful future context.

Check

  • Frame set before obs began (not wandering)
  • Raw obs recorded as facts before interpretation
  • ≥5 discrete obs w/ specific evidence
  • Interpretation separated from obs
  • ≥1 surprising/contrarian finding
  • Archive specific enough another observer can verify

Traps

  • Premature intervention: see + fix immediately → lose broader pattern
  • Obs bias: see expected, not present. Expectations filter → frame mitigates not eliminates
  • Analysis paralysis: obs endlessly → no action. Set time/data limit, commit to conclude
  • Narrative imposition: connecting obs even when connections weak. Not all coherent — disconnected = valid
  • Familiarity ≠ understanding: "seen before" ≠ "know why". False confidence
  • Ignore own reactions: emotional/cognitive reactions = data. Confusion/boredom/alarm = signal

  • observe-guidance — human-guidance variant
  • learn — obs feeds learning w/ raw data
  • listen — outward to user; obs broader to any system
  • remote-viewing — intuitive, validatable through obs
  • meditate — sustained attention capacity
  • awareness — threat-focused; obs curiosity-driven

GitHub リポジトリ

pjt222/agent-almanac
パス: i18n/caveman-ultra/skills/observe
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

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