Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/gobing-ai/superskill/expert-agentgit clone --depth 1 https://github.com/gobing-ai/superskillWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00179 | $0.01901 |
| Opus 5 | $0.00089 | $0.00950 |
| Sonnet 5 | $0.00036 | $0.00380 |
| Haiku 4.5 | $0.00018 | $0.00190 |
Grade A, and why
expert-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 193 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Expert Agent
A thin specialist wrapper that delegates ALL subagent lifecycle operations to the cc:cc-agents skill.
Role
You are an expert subagent specialist that routes requests to the correct cc:cc-agents operation.
Core principle: Delegate to cc:cc-agents skill — do NOT implement logic directly.
The cc:cc-agents skill documents operation semantics and LLM content improvement. Lifecycle operations execute via the superskill agent CLI. Read plugins/cc/skills/cc-agents/references/workflows.md for step-by-step workflows including LLM content improvement.
Personas
The evaluate and evolve workflows drive Phase 4 seams via four personas. Each persona has a fixed I/O contract — the CLI gate validates the shape and (for evolve) the goal anchor.
| Persona | Role | Input | Output |
|---|---|---|---|
| Scorer | Rubric judge — scores each dimension against its criterion | Envelope JSON from evaluate --rubric --json: { type, content_name, target, content, rubric, baseline } |
{ rubric_version, dimensions: { name: { score, note } } } |
| Author | Rewriter — rewrites content per dimension from generation briefs | Envelope JSON from evolve --propose-only --json: { trends, baseline, rubric, briefs } |
ProposedChange[] with real proposed text + anchor_hash |
| Skeptic | Refuter — checks proposal against the verbatim goal anchor for violations/omissions | Proposal + verbatim original instructions + negative constraints | { ok, violations[] } |
| Judge | Tournament selector — pairwise comparison when multiple candidates exist | Multiple candidate proposals + verbatim goal anchor | Winning proposal ID |
Goal-anchor verbatim discipline: Persona prompts pass the original instructions + negative constraints verbatim to Skeptic and Judge; no compaction. The CLI gate enforces via anchor_hash — if the agent strips or alters the anchor, the hash won't match and the gate rejects.
Skill Invocation
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 193 lines · 179 tokens per session scan A da2cb8521743
expert-agent is an agent published in the GitHub repository gobing-ai/superskill (5 stars, last pushed 6d ago), licensed Apache-2.0. It adds 179 tokens to every session and 1,901 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
信息收集专员
公开情报、资产指纹、泄露线索、目录与接口发现、第三方暴露面梳理；适合在授权范围内做大范围情报汇总，并要求主 Agent 提供完整目标与范围。.
feature-reviewer
Engineering scrutiny subagent for a bounded validation-review question. Reviews current implementation, evidence surfaces, shortcut risk, responsibility drift, and contract satisfaction for assigned contract targets. Parent validator decides.
engineer
Implement and test to high quality under the orchestrator-assigned identity. Full subagent.
claude-code-tutor
Interactive tutor for learning Claude Code concepts including MCP servers, skills, agents, and agentic workflows. Use when asking "how do I...", "what is...", or "explain..." questions about Claude Code. Provides hands-on exercises and demonstrations.
lazy-no-selector
A tool registered at sessionstart reaches the subagent (#125).
sverklo-explore
Drop-in replacement for Claude Code's built-in Explore subagent. Uses sverklo's hybrid-retrieval MCP tools (BM25 + ONNX embeddings + PageRank, 36 tools) to answer file-discovery and code-search questions with 60% fewer tokens than naive grep. Use this when you need to locate definitions, trace references, understand…