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ww-w-aiww-w-ai/bkit-claude-code/skills/btw/SKILL.md

btw

Skill605 starsChanged 3 months agoApache-2.0View on GitHub

By-The-Way: capture improvement ideas the moment they surface, without derailing the task in progress. Triggers: /bkit:btw, /bkit:btw list, /bkit:btw analyze, /bkit:btw promote, /bkit:btw stats, btw, suggestion, improve, idea, feedback

3 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 0 are distinctive, and 6 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read .bkit/btw-suggestions.json (create if not exists)

    line 32
  2. Very specific:

    Read all pending suggestions from .bkit/btw-suggestions.json

    line 80
  3. Very specific:

    When /btw is used during a CTO Team session (/pdca team):

    line 171
  4. Very specific:

    Check if team session is active via .bkit/runtime/agent-state.json

    line 174
  5. Very specific:

    If active: set teamContext.isTeamSession = true and populate phase/role/pattern

    line 175
  6. Very specific:

    If not active: set teamContext.isTeamSession = false (default behavior)

    line 176

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

/btw - By-The-Way Suggestion Collector

작업 중 "이거 스킬로 만들면 좋겠다", "이 패턴 자동화하면 좋겠다" 등의 개선 제안을 즉시 기록하고 관리하는 도구.

Commands

/btw {suggestion} - Record a suggestion

  1. Read .bkit/btw-suggestions.json (create if not exists)
  2. Generate next ID: btw-NNN (zero-padded, sequential)
  3. Create suggestion entry:
    {
      "id": "btw-001",
      "timestamp": "ISO-8601",
      "suggestion": "{user input}",
      "context": {
        "file": "{current working file if identifiable}",
        "pdcaPhase": "{current PDCA phase from getPdcaStatusView() or null}",
        "feature": "{current feature or null}"
      },
      "category": "auto-detect",
      "status": "pending",
      "promotedTo": null,
      "priority": null,
      "teamContext": {
        "isTeamSession": false,
        "phase": "{PDCA phase or null}",
        "role": "{teammate role that discovered this, or 'user'}",
        "pattern": "{orchestration pattern or null}"
      }
    }
  4. Auto-detect category from suggestion text:
    • skill-request: mentions "skill", "스킬", "자동화", "automate"
    • bug-pattern: mentions "bug", "버그", "오류", "error", "fix"
    • improvement: mentions "개선", "improve", "better", "refactor"
    • documentation: mentions "문서", "doc", "설명", "explain"
    • general: default
  5. Update stats.total count
  6. Respond: "Recorded btw-{NNN}: {truncated suggestion}. Use /btw list to view all."

/btw list - List all suggestions

  1. Read .bkit/btw-suggestions.json
  2. Display table:
    ID       | Status   | Category       | Suggestion (truncated)
    ---------|----------|----------------|----------------------
    btw-001  | pending  | skill-request  | @Flow 모델에서 옵션 목록을 자동...
    btw-002  | promoted | improvement    | DataProxy 패턴에 검증 로직을...
  3. Show summary: Total: N | Pending: N | Promoted: N | Dismissed: N

/btw analyze - Analyze suggestions for skill candidates

  1. Read all pending suggestions from .bkit/btw-suggestions.json
  2. Group by category and find patterns:
    • Cluster similar suggestions (keyword overlap)
    • Count frequency of similar topics
    • Identify suggestions that map to existing bkit skills vs. new skill needs
  3. For each skill candidate:
    • Estimate skill classification: workflow vs capability
    • Suggest skill name and description
    • Reference source suggestion IDs
  4. Output analysis:
    Skill Candidates from /btw Analysis
    =====================================
    
    1. [NEW SKILL] hunikflow-validation (capability)
       Based on: btw-001, btw-005, btw-008
       Frequency: 3 mentions
       Description: Validation pattern guide for @Flow entities
    
    2. [EXISTING SKILL ENHANCEMENT] code-review
       Based on: btw-003
       Suggestion: Add DataProxy-specific review rules
  5. Save analysis timestamp to stats.lastAnalyzed

/btw promote {id} - Promote suggestion to skill creation

  1. Find suggestion by ID in .bkit/btw-suggestions.json
  2. Validate status is "pending" (cannot promote already promoted/dismissed)
  3. Update suggestion:
    • status: "promoted"
    • promotedTo: skill name (derived from suggestion)
  4. Trigger skill-create workflow with context from the suggestion:
    • Pass suggestion text as skill description seed
    • Pass context (file, feature) as project context
  5. Respond: "Promoted btw-{id} -> skill-create pipeline. Run /skill-create to continue."

/btw stats - Show statistics

  1. Read .bkit/btw-suggestions.json
  2. Calculate and display:
    /btw Statistics
    ===============
    Total suggestions: 12
    By status: pending=8, promoted=3, dismissed=1
    By category: skill-request=5, improvement=4, bug-pattern=2, general=1
    Promotion rate: 25.0%
    Last analyzed: 2026-03-13T10:00:00Z
    Top keywords: @Flow(3), DataProxy(2), validation(2)

Data File: .bkit/btw-suggestions.json

Initialize with this structure if file does not exist:

{
  "version": "1.0",
  "suggestions": [],
  "stats": {
    "total": 0,
    "promoted": 0,
    "dismissed": 0,
    "lastAnalyzed": null
  }
}

Category Auto-Detection Rules

PatternCategory
skill, 스킬, automate, 자동화, command, 명령skill-request
bug, 버그, error, 오류, fix, 수정bug-pattern
improve, 개선, better, refactor, 리팩토링, optimizeimprovement
doc, 문서, explain, 설명, readme, guidedocumentation
(default)general

Integration Points

  • PDCA Context: Reads the phase and feature through getPdcaStatusView() (lib/pdca/status.js), which covers a phase that only its documents evidence. .bkit/state/memory.json — the migrated .bkit-memory.json — carries the 9-phase pipeline status, not the PDCA phase.
  • skill-create: /btw promote triggers skill-create workflow
  • skill-needs-extractor: /btw analyze results feed into gap analysis
  • CTO Team: Phase transition triggers btw summary (see below)

CTO Team Integration

When /btw is used during a CTO Team session (/pdca team):

Auto-Detection

  • Check if team session is active via .bkit/runtime/agent-state.json
  • If active: set teamContext.isTeamSession = true and populate phase/role/pattern
  • If not active: set teamContext.isTeamSession = false (default behavior)

Phase Transition Hook

CTO Lead automatically reads btw-suggestions.json at every phase transition:

  • 0 pending: Silent skip (no output, no turns spent)
  • 1+ pending: Brief summary (top 3, category counts) in 1-2 turns
  • CTO does NOT auto-promote — user decides via /btw promote {id}

Session End

cto-stop.js hook outputs btw stats at session end:

  • Total suggestions collected during session
  • Category breakdown
  • Promotion rate

teamContext Field

Added to each suggestion entry when recorded during a team session:

"teamContext": {
  "isTeamSession": true,
  "phase": "do",
  "role": "user",
  "pattern": "swarm"
}

This enables /btw analyze to group suggestions by PDCA phase and identify phase-specific patterns.

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