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.
git clone --depth 1 https://github.com/joneqian/claude-skills-suiteWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/joneqian/claude-skills-suite/evolve)<a href="https://agentmods.dev/commands/joneqian/claude-skills-suite/evolve"><img src="https://agentmods.dev/badge/commands/joneqian/claude-skills-suite/evolve/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/joneqian/claude-skills-suite/evolve"><img src="https://agentmods.dev/badge/commands/joneqian/claude-skills-suite/evolve.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00013 | $0.01165 |
| Opus 5 | $0.00006 | $0.00583 |
| Sonnet 5 | $0.00003 | $0.00233 |
| Haiku 4.5 | $0.00001 | $0.00117 |
Grade A, and why
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 8d 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.
This is a copy
100% identical to evolve — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evolve Command
Implementation
python3 ~/.claude/skills/continuous-learning-v2/scripts/instinct-cli.py evolve [--generate]
Analyzes instincts and clusters related ones into higher-level structures:
- Commands: When instincts describe user-invoked actions
- Skills: When instincts describe auto-triggered behaviors
- Agents: When instincts describe complex, multi-step processes
Usage
/evolve # Analyze all instincts and suggest evolutions
/evolve --domain testing # Only evolve instincts in testing domain
/evolve --dry-run # Show what would be created without creating
/evolve --threshold 5 # Require 5+ related instincts to cluster
Evolution Rules
→ Command (User-Invoked)
When instincts describe actions a user would explicitly request:
- Multiple instincts about "when user asks to..."
- Instincts with triggers like "when creating a new X"
- Instincts that follow a repeatable sequence
Example:
new-table-step1: "when adding a database table, create migration"new-table-step2: "when adding a database table, update schema"new-table-step3: "when adding a database table, regenerate types"
→ Creates: /new-table command
→ Skill (Auto-Triggered)
When instincts describe behaviors that should happen automatically:
- Pattern-matching triggers
- Error handling responses
- Code style enforcement
Example:
prefer-functional: "when writing functions, prefer functional style"use-immutable: "when modifying state, use immutable patterns"avoid-classes: "when designing modules, avoid class-based design"
→ Creates: functional-patterns skill
→ Agent (Needs Depth/Isolation)
When instincts describe complex, multi-step processes that benefit from isolation:
- Debugging workflows
- Refactoring sequences
- Research tasks
Example:
debug-step1: "when debugging, first check logs"debug-step2: "when debugging, isolate the failing component"debug-step3: "when debugging, create minimal reproduction"debug-step4: "when debugging, verify fix with test"
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.
- 8d ago First seen · 187 lines · 13 tokens per session scan A 88ece7568f8f
evolve is a command published in the GitHub repository joneqian/claude-skills-suite (32 stars, last pushed 7mo ago), licensed MIT. It adds 13 tokens to every session and 1,165 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to evolve, differing in 0 lines, and is treated as a copy.
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.