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ccs-delegation

Auto-activate CCS CLI delegation for deterministic tasks. Parses user input, auto-selects optimal profile (glm/kimi/custom) from ~/.ccs/config.json, enhances prompts with context, executes via `ccs {profile} -p "task"` or `ccs {profile}:continue`, and reports results. Triggers on "use ccs [task]" patterns, typo/test/refactor keywords. Excludes complex architecture, security-critical code, performance optimization, breaking changes.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

설치 방법 보기

포함된 파일(3)

  • SKILL.md7.0 KB
  • CLAUDE.md.template647 B
  • references/troubleshooting.md7.6 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

CCS Delegation

Delegate deterministic tasks to cost-optimized models via CCS CLI.

Core Concept

Execute tasks via alternative models using:

  • Initial delegation: ccs {profile} -p "task"
  • Session continuation: ccs {profile}:continue -p "follow-up"

Profile Selection:

  • Auto-select from ~/.ccs/config.json via task analysis
  • Profiles: glm (cost-optimized), kimi (long-context/reasoning), custom profiles
  • Override: --{profile} flag forces specific profile

User Invocation Patterns

Users trigger delegation naturally:

  • "use ccs [task]" - Auto-select best profile
  • "use ccs --glm [task]" - Force GLM profile
  • "use ccs --kimi [task]" - Force Kimi profile
  • "use ccs:continue [task]" - Continue last session

Examples:

  • "use ccs to fix typos in README.md"
  • "use ccs to analyze the entire architecture"
  • "use ccs --glm to add unit tests"
  • "use ccs:continue to commit the changes"

Agent Response Protocol

For /ccs [task]:

  1. Parse override flag

    • Scan task for pattern: --(\w+)
    • If match: profile = match[1], remove flag from task, skip to step 5
    • If no match: continue to step 2
  2. Discover profiles

    • Read ~/.ccs/config.json using Read tool
    • Extract Object.keys(config.profiles) → availableProfiles[]
    • If file missing → Error: "CCS not configured. Run: ccs doctor"
    • If empty → Error: "No profiles in config.json"
  3. Analyze task requirements

    • Scan task for keywords:
      • /(think|analyze|reason|debug|investigate|evaluate)/i → needsReasoning = true
      • /(architecture|entire|all files|codebase|analyze all)/i → needsLongContext = true
      • /(typo|test|refactor|update|fix)/i → preferCostOptimized = true
  4. Select profile

    • For each profile in availableProfiles: classify by name pattern (see Profile Characteristic Inference table)
    • If needsReasoning: filter profiles where reasoning=true → prefer kimi
    • Else if needsLongContext: filter profiles where context=long → prefer kimi
    • Else: filter profiles where cost=low → prefer glm
    • selectedProfile = filteredProfiles[0]
    • If filteredProfiles.length === 0: fallback to glm if exists, else first available
    • If no profiles: Error
  5. Enhance prompt

    • If task mentions files: gather context using Read tool
    • Add: file paths, current implementation, expected behavior, success criteria
    • Preserve slash commands at task start (e.g., /cook, /commit)
  6. Execute delegation

    • Run: ccs {selectedProfile} -p "$enhancedPrompt" via Bash tool
  7. Report results

    • Log: "Selected {profile} (reason: {reasoning/long-context/cost-optimized})"
    • Report: Cost (USD), Duration (sec), Session ID, Exit code

For /ccs:continue [follow-up]:

  1. Detect profile

    • Read ~/.ccs/delegation-sessions.json using Read tool
    • Find most recent session (latest timestamp)
    • Extract profile name from session data
    • If no sessions → Error: "No previous delegation. Use /ccs first"
  2. Parse override flag

    • Scan follow-up for pattern: --(\w+)
    • If match: profile = match[1], remove flag from follow-up, log profile switch
    • If no match: use detected profile from step 1
  3. Enhance prompt

    • Review previous work (check what was accomplished)
    • Add: previous context, incomplete tasks, validation criteria
    • Preserve slash commands at start
  4. Execute continuation

    • Run: ccs {profile}:continue -p "$enhancedPrompt" via Bash tool
  5. Report results

    • Report: Profile, Session #, Incremental cost, Total cost, Duration, Exit code

Decision Framework

Delegate when:

  • Simple refactoring, tests, typos, documentation
  • Deterministic, well-defined scope
  • No discussion/decisions needed

Keep in main when:

  • Architecture/design decisions
  • Security-critical code
  • Complex debugging requiring investigation
  • Performance optimization
  • Breaking changes/migrations

Profile Selection Logic

Task Analysis Keywords (scan task string with regex):

PatternVariableExample
/(think|analyze|reason|debug|investigate|evaluate)/ineedsReasoning = true"think about caching"
/(architecture|entire|all files|codebase|analyze all)/ineedsLongContext = true"analyze all files"
/(typo|test|refactor|update|fix)/ipreferCostOptimized = true"fix typo in README"

Profile Characteristic Inference (classify by name pattern):

Profile PatternCostContextReasoning
/^glm/ilowstandardfalse
/^kimi/imediumlongtrue
/^claude/ihighstandardfalse
otherslowstandardfalse

Selection Algorithm (apply filters sequentially):

profiles = Object.keys(config.profiles)
classified = profiles.map(p => ({name: p, ...inferCharacteristics(p)}))

if (needsReasoning):
  filtered = classified.filter(p => p.reasoning === true).sort(['kimi'])
else if (needsLongContext):
  filtered = classified.filter(p => p.context === 'long').sort(['kimi'])
else:
  filtered = classified.filter(p => p.cost === 'low').sort(['glm', ...])

selected = filtered[0] || profiles.find(p => p === 'glm') || profiles[0]
if (!selected): throw Error("No profiles configured")

log("Selected {selected} (reason: {reasoning|long-context|cost-optimized})")

Override Logic:

  • Parse task for /--(\w+)/. If match: profile = match[1], remove from task, skip selection

Example Delegation Tasks

Good candidates:

  • "/ccs add unit tests for UserService using Jest" → Auto-selects: glm (simple task)
  • "/ccs analyze entire architecture in src/" → Auto-selects: kimi (long-context)
  • "/ccs think about the best database schema design" → Auto-selects: kimi (reasoning)
  • "/ccs --glm refactor parseConfig to use destructuring" → Forces: glm (override)

Bad candidates (keep in main):

  • "implement OAuth" (too complex, needs design)
  • "improve performance" (requires profiling)
  • "fix the bug" (needs investigation)

Execution

Commands:

  • /ccs "task" - Intelligent delegation (auto-select profile)
  • /ccs --{profile} "task" - Force specific profile
  • /ccs:continue "follow-up" - Continue last session (auto-detect profile)
  • /ccs:continue --{profile} "follow-up" - Continue with profile switch

Agent via Bash:

  • Auto: ccs {auto-selected} -p "task"
  • Continue: ccs {detected}:continue -p "follow-up"

References

Template: CLAUDE.md.template - Copy to user's CLAUDE.md for auto-delegation config Troubleshooting: references/troubleshooting.md

리뷰

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