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/tunahanaliozturk/atelierWrote 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/tunahanaliozturk/atelier/validate)<a href="https://agentmods.dev/commands/tunahanaliozturk/atelier/validate"><img src="https://agentmods.dev/badge/commands/tunahanaliozturk/atelier/validate/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/tunahanaliozturk/atelier/validate"><img src="https://agentmods.dev/badge/commands/tunahanaliozturk/atelier/validate.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 | $0.00020 | $0.00208 |
| Opus 5 | $0.00010 | $0.00104 |
| Sonnet 5 | $0.00004 | $0.00042 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
validate 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 9d 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.
What it actually says
Read the most recently modified mission file under .atelier/missions/ and parse it with
parseMission (lib/mission.mjs). Read the agent registry from agents/ with readRegistry
(lib/registry.mjs), or use the registry the SessionStart hook put in context. Run
validateAgainstRegistry (lib/validate.mjs).
- List the findings grouped as errors first, then warnings.
- End with a summary line: "N errors, M warnings", or "all checks passed" when there are none.
- This is advisory and never blocks dispatch. Errors are consistency or referential problems (duplicate id, invalid status, unknown dependency, dependency cycle, or an agent not in the registry). Warnings are coverage gaps (stack layers with no agent).
- If there is no mission file, say there is no active mission.
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.
- 9d ago First seen · 16 lines · 20 tokens per session scan A 3ceb1111df07
validate is a command published in the GitHub repository tunahanaliozturk/atelier (1 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 208 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
bug
Reproduce then TDD-fix a ready-for-agent bug ticket in this checkout. Web bugs get a browser repro first.
decree
Issue a decree. Seats the organization on first use, then dispatches the teams.
bob-new
Provision a well-formed task onto the Bob board from a rough description.
report
The full account of the current decree — every figure verified before stated.
assess
Run an AI literacy assessment — scan the repo for evidence, ask clarifying questions, produce a timestamped assessment document, apply immediate habitat fixes, recommend workflow changes, capture a reflection, and add a literacy level badge to the README.
harness-affordance
Manage the project's affordance inventory — declared tools the agent can invoke, the identity each tool runs under, and the audit trail each tool produces. Subcommands - discover (scan config to produce a draft inventory), add (promote a draft into HARNESS.md with governance metadata), review (re-validate one…