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ccs-delegation

kaitranntt · Инструменти

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]" pa

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Теми: ai-gateway · anthropic-api · claude · claude-code · cli-tool · cliproxyapi · developer-productivity · gemini · github-copilot · multi-account · nodejs · oauth · openrouter · profile-switching · react-dashboard

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MIT
Последна проверка на записа
22.09.2026 г.

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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)

Целият SKILL.md в GitHub