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/curt-park/autology/eval-behaviorgit clone --depth 1 https://github.com/Curt-Park/autologyWrote 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/curt-park/autology/eval-behavior)<a href="https://agentmods.dev/commands/curt-park/autology/eval-behavior"><img src="https://agentmods.dev/badge/commands/curt-park/autology/eval-behavior.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 | $0.00021 | $0.01067 |
| Opus 5 | $0.00010 | $0.00534 |
| Sonnet 5 | $0.00004 | $0.00213 |
| Haiku 4.5 | $0.00002 | $0.00107 |
Grade A, and why
eval-behavior 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 4d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autology Behavioral Eval
Run behavioral evals for the skill named $ARGUMENTS.
Setup
Read these files before proceeding:
skills/$ARGUMENTS/SKILL.md— the skill instructionsskills/$ARGUMENTS/evals/evals.json— eval cases with prompts and assertions
Workspace: $ARGUMENTS-workspace/ (create if needed, overwrite previous runs)
Step 1: Run each eval case
For each case in evals.json, run it twice in the same turn using the Agent tool — once with the skill, once without. Launch all pairs in parallel.
Always use isolation: "worktree" on every agent. Each agent runs in its own isolated git worktree — a full copy of the repository at the current HEAD. This means:
docs/in the worktree is a clean copy; agents can freely write to it without contaminating the real repo or each other's state- No manual sandbox setup needed
- After the agent completes, the worktree path is returned in the result (use it to read output files)
⚠️ Absolute paths bypass isolation. Worktree isolation only works when agents use relative paths. If an agent writes to an absolute path (e.g. the real repo's docs/ directory), it lands outside the worktree and contaminates the shared repo. Every agent prompt must include the instruction below to prevent this.
Fixture files: If the eval requires a file to pre-exist (e.g., docs/api-gateway.md that the task says "assume exists"), commit it to skills/$ARGUMENTS/evals/fixtures/ in the repo. The agent prompt should instruct the agent to copy it to docs/ at the start: "Copy skills/$ARGUMENTS/evals/fixtures/api-gateway.md to docs/ before starting."
With-skill agent prompt:
Execute this task following the skill instructions below.
SKILL INSTRUCTIONS:
<paste full contents of skills/$ARGUMENTS/SKILL.md here>
TASK: <eval prompt>
The project knowledge base is at docs/. Save:
- Your complete response → $ARGUMENTS-workspace/<eval-name>/with_skill/response.txt
- A step-by-step log of every tool you used → $ARGUMENTS-workspace/<eval-name>/with_skill/transcript.md
Create directories as needed.
IMPORTANT: Use only relative paths for all file operations (docs/, $ARGUMENTS-workspace/, etc.).
Do NOT write to any absolute path — absolute paths bypass your isolated worktree and contaminate the shared repo.
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.
- 4d ago First seen · 109 lines · 0 tokens per session scan A c605283e21c9
eval-behavior is a command published in the GitHub repository Curt-Park/autology (24 stars, last pushed 5mo ago), licensed MIT. It adds 21 tokens to every session and 1,067 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 2026-08-30.
Other commands, from other repositories
configure
View or modify MAMA configuration (database, embedding model, tier status, security settings).
checkpoint
Save the current session state for later resumption.
decision
Save a decision or insight to MAMA's long-term memory.
search
Search decisions and checkpoints (semantic or list recent).
resume
Resume work from the last saved session checkpoint.
add-entry
Research a GitHub repo and add a curated entry to data/entries with real metadata and honest notes.