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 commands/gobing-ai/superskill/agent-evolvegit 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 | $0.00013 | $0.00891 |
| Opus 5 | $0.00006 | $0.00445 |
| Sonnet 5 | $0.00003 | $0.00178 |
| Haiku 4.5 | $0.00001 | $0.00089 |
Grade A, and why
agent-evolve 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- skill-evolve — 86% identical, 33 lines differ
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Evolve
Wraps cc:cc-agents skill.
Analyze agent quality over time, draft heuristic proposals for declining/flat-low dimensions, apply proposals through the double-loop gate, and rollback to prior versions via saved snapshots. Delegates to cc:cc-agents skill.
When to Use
- Analyze trends, data sources, and patterns without writing a proposal (
--analyze) - Generate proposals after evaluation drift or repeated review feedback (
--propose-only) - Apply proposals through the deterministic double-loop gate with backup and rollback (
--accept,--rollback) - Track applied versions over time (
--history)
Arguments
| Argument | Description | Default |
|---|---|---|
<name> |
Name of the agent | (required) |
--analyze |
Print trend table, score/grade, data-source inventory, and pattern summary | false |
--from <date> |
Analyze evaluations since date (ISO 8601) | latest |
--propose-only |
Draft proposals without applying | false |
--accept <id> |
Apply a saved proposal by ID | - |
--reject <id> |
Reject a saved proposal by ID | - |
--history |
List applied proposal versions from the store | false |
--rollback <id> |
Restore a prior version by proposal_id (requires --confirm) |
- |
--confirm |
Confirm a destructive operation (required for --rollback) |
false |
--ingest <file> |
Agent-authored proposal JSON (ingest-in mode) | - |
--json |
Output machine-readable JSON (envelope-out with --propose-only) |
false |
--margin <n> |
Δ-margin gate threshold for accept (default 0.05) | 0.05 |
--eval-gate |
Enable the empirical behavior gate when eval cases exist | false |
--target |
Target platform | claude |
Examples
# Generate persisted proposals
/cc:agent-evolve ./agents/my-agent.md --propose-only
# Analyze trends without writing a proposal
/cc:agent-evolve ./agents/my-agent.md --analyze
# Apply a proposal
/cc:agent-evolve ./agents/my-agent.md --accept agent-evolve-2026-06-21-001
# List applied versions
/cc:agent-evolve ./agents/my-agent.md --history
# Rollback to a prior version
/cc:agent-evolve ./agents/my-agent.md --rollback agent-evolve-2026-06-21-001 --confirm
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 · 81 lines · 13 tokens per session scan A f29de80d7183
agent-evolve is a command published in the GitHub repository gobing-ai/superskill (5 stars, last pushed 6d ago), licensed Apache-2.0. It adds 13 tokens to every session and 891 once invoked, about $0.0001 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 commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.