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/mturac/everything-openai-codex/evolvegit clone --depth 1 https://github.com/mturac/everything-openai-codexWrote 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/mturac/everything-openai-codex/evolve)<a href="https://agentmods.dev/commands/mturac/everything-openai-codex/evolve"><img src="https://agentmods.dev/badge/commands/mturac/everything-openai-codex/evolve.svg" alt="Measured on agentmods" 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 | $0.00008 | $0.00245 |
| Opus 5 | $0.00004 | $0.00122 |
| Sonnet 5 | $0.00002 | $0.00049 |
| Haiku 4.5 | $0.00001 | $0.00024 |
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 yesterday.
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
86% identical to evolve — 12 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.
What it actually says
Evolve Command
Analyze and evolve instincts in continuous-learning-v2: $ARGUMENTS
Your Task
Run:
python3 "${CODEX_PLUGIN_ROOT}/skills/continuous-learning-v2/scripts/instinct-cli.py" evolve $ARGUMENTS
If CODEX_PLUGIN_ROOT is unavailable, use:
python3 ~/.codex/skills/continuous-learning-v2/scripts/instinct-cli.py evolve $ARGUMENTS
Supported Args (v2.1)
- no args: analysis only
--generate: also generate files underevolved/{skills,commands,agents}
Behavior Notes
- Uses project + global instincts for analysis.
- Shows skill/command/agent candidates from trigger and domain clustering.
- Shows project -> global promotion candidates.
- With
--generate, output path is:- project context:
~/.codex/homunculus/projects/<project-id>/evolved/ - global fallback:
~/.codex/homunculus/evolved/
- project context:
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.
- yesterday First seen · 37 lines · 8 tokens per session scan A 8672192ea174
evolve is a command published in the GitHub repository mturac/everything-openai-codex (89 stars, last pushed 11d ago), licensed MIT. It adds 8 tokens to every session and 245 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to evolve, differing in 12 lines, and is treated as a copy.
Other commands, from other repositories
feature
Orchestrate a complete feature through discovery, spec, implementation, and review.
research
Research a technical or product question.
selfloop
Start or control a persistent SIPS loop whose only objective is improving SIPS and the agent operating it through measured, verified iterations.
dev-planner
Generate or update DEV-PLAN.md with phased development plan from Product-Spec.md.
patterns
Show the full agentpatterns report — success rate, approach→outcome correlation, top patterns.
verify
Spawn a fresh-context verifier subagent to check completed work against its specification before trusting it.