Agent skill

aget-study-topic

Research a topic across the knowledge base before implementation. Searches L-docs, patterns, PROJECT_PLANs, SOPs, and governance for relevant context.

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Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/aget-study-topic-aget-framework-template-executive-a

SKILL.md

/aget-study-topic

Focused KB research on a specific topic before proposing changes or starting implementation.

Purpose

Per L335 (Memory Architecture) and PATTERN_step_back_review_kb, this skill enables targeted research across the knowledge base. Use it to gather context and precedents before implementing changes.

Input

$ARGUMENTS - The topic to research (required)

Examples:

  • /aget-study-topic release — Research release-related artifacts
  • /aget-study-topic skills — Research skill-related context
  • /aget-study-topic L477 — Find references to specific L-doc

Execution

Step 1: Validate Input

If no topic provided, prompt user:

Topic required

Usage: /aget-study-topic <topic>

Example: /aget-study-topic release

Step 2: Run Study Up Script

bash
python3 scripts/study_up.py --topic "$ARGUMENTS"

The script searches 5 KB areas:

  • L-docs (.aget/evolution/L*.md)
  • Patterns (docs/patterns/PATTERN_*.md)
  • PROJECT_PLANs (planning/PROJECT_PLAN*.md)
  • SOPs (sops/SOP_*.md)
  • Governance (governance/*.md)

Step 3: Present Findings

Display results in this format:

=== /aget-study-topic: {topic} ===

L-docs Found: [count]
  - L###: {title} ({match_count} matches)
  - ...

Patterns Found: [count]
  - PATTERN_{name}: {matches}

PROJECT_PLANs Found: [count]
  - {plan_name}: {status}

SOPs Found: [count]
  - SOP_{name}: {matches}

Governance: [count]
  - {file}: {matches}

Recommendation:
  [coverage assessment based on findings]

Step 4: Suggest Next Steps

Based on findings, suggest:

  • Specific L-docs to read in detail
  • Active PROJECT_PLANs to be aware of
  • Governance constraints that apply

Output Modes

Human-Readable (default)

bash
python3 scripts/study_up.py --topic "$ARGUMENTS"

JSON (programmatic)

bash
python3 scripts/study_up.py --topic "$ARGUMENTS" --json

Quiet (minimal)

bash
python3 scripts/study_up.py --topic "$ARGUMENTS" --quiet

Constraints

  • C1: Topic argument is REQUIRED. Do not run without a topic.
  • C2: Read-only operation. Never modify KB files.
  • C3: Present findings objectively. Let user decide relevance.
  • C4: If topic returns 0 results, report "No matches found" and suggest alternative search terms.

When to Use

Scenario Use /aget-study-topic
Before implementing a feature Yes — check for related patterns
Before creating L-doc Yes — avoid duplicating existing learnings
User asks about existing work Yes — surface relevant artifacts
Quick file lookup No — use grep/glob directly

Related Skills

  • /aget-wake-up — Session initialization (broader context load)
  • /aget-check-health — Health verification
  • /aget-check-evolution — Evolution directory health
  • /aget-record-lesson — Capture new learnings

Traceability

Link Reference
Script scripts/study_up.py
Spec AGET_SESSION_SPEC.md (CAP-SESSION-007)
Pattern PATTERN_step_back_review_kb.md
L-docs L335 (Memory Architecture), L187 (Silent Execution)
Tests tests/test_session_protocol.py::TestStudyUpProtocol (6 tests)

aget-study-topic v1.0.0 Category: Research Based on CAP-SESSION-007 (Study Up Protocol)

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