Install
$ agentstack add skill-spideynolove-claude-dotfiles-ccs-delegation ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
> Note: Converted from Claude Skill.
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.jsonvia 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]:
- 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
- Discover profiles
- Read
~/.ccs/config.jsonusing 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"
- 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
- Select profile
- For each profile in
availableProfiles: classify by name pattern (see Profile Characteristic Inference table) - If
needsReasoning: filter profiles wherereasoning=true→ prefer kimi - Else if
needsLongContext: filter profiles wherecontext=long→ prefer kimi - Else: filter profiles where
cost=low→ prefer glm selectedProfile = filteredProfiles[0]- If
filteredProfiles.length === 0: fallback toglmif exists, else first available - If no profiles: Error
- 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)
- Execute delegation
- Run:
ccs {selectedProfile} -p "$enhancedPrompt"via Bash tool
- Report results
- Log: "Selected {profile} (reason: {reasoning/long-context/cost-optimized})"
- Report: Cost (USD), Duration (sec), Session ID, Exit code
For /ccs:continue [follow-up]:
- Detect profile
- Read
~/.ccs/delegation-sessions.jsonusing Read tool - Find most recent session (latest timestamp)
- Extract profile name from session data
- If no sessions → Error: "No previous delegation. Use /ccs first"
- Parse override flag
- Scan follow-up for pattern:
--(\w+) - If match:
profile = match[1], remove flag from follow-up, log profile switch - If no match: use detected profile from step 1
- Enhance prompt
- Review previous work (check what was accomplished)
- Add: previous context, incomplete tasks, validation criteria
- Preserve slash commands at start
- Execute continuation
- Run:
ccs {profile}:continue -p "$enhancedPrompt"via Bash tool
- 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):
| Pattern | Variable | Example | |---------|----------|---------| | /(think\|analyze\|reason\|debug\|investigate\|evaluate)/i | needsReasoning = true | "think about caching" | | /(architecture\|entire\|all files\|codebase\|analyze all)/i | needsLongContext = true | "analyze all files" | | /(typo\|test\|refactor\|update\|fix)/i | preferCostOptimized = true | "fix typo in README" |
Profile Characteristic Inference (classify by name pattern):
| Profile Pattern | Cost | Context | Reasoning | |----------------|------|---------|-----------| | /^glm/i | low | standard | false | | /^kimi/i | medium | long | true | | /^claude/i | high | standard | false | | others | low | standard | false |
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
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: spideynolove
- Source: spideynolove/claude-dotfiles
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.