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 skills add martinffx/atelier --skill spec-loopgit clone --depth 1 https://github.com/martinffx/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/skills/martinffx/atelier/spec-loop)<a href="https://agentmods.dev/skills/martinffx/atelier/spec-loop"><img src="https://agentmods.dev/badge/skills/martinffx/atelier/spec-loop/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/skills/martinffx/atelier/spec-loop"><img src="https://agentmods.dev/badge/skills/martinffx/atelier/spec-loop.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 | $0.00066 | $0.01196 |
| Opus 5.5 | $0.00026 | $0.00478 |
| Sonnet 5.5 | $0.00013 | $0.00239 |
| Haiku 4.5 | $0.00007 | $0.00120 |
Grade A, and why
spec-loop 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.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spec Loop
Drive an approved Spec-backed Plan to a draft PR without stopping for the human. The main agent
only drives; fresh subagents implement and review. Never run code-review rs in this loop.
Announce at start: "I'm using the spec-loop skill to run this plan to a draft PR."
This skill makes no design decisions. A finding or blocker that needs a plan change goes back to
spec-plan; a design change goes back to spec-brainstorm.
Start
Runs on every invocation, including a resume.
- If
design.mdorplan.jsonis missing, stop and use spec-implement. Otherwise follow spec-implement Prerequisites and "Load and Review the Plan" while the human is present. - Stop if the tree is dirty or the test suite is not green.
- Ask one authorization question naming each action. The answer is the explicit authorization
code-commit and code-pull-request require.
- commit after every batch and after the final fix
- push to
<remote>/<branch>, without force - open a draft PR with code-pull-request's Create flow
- budget: at most N batches (plan task count / 3, rounded up, plus 1); stop when the same task or test fails twice
- cost: one batch reviewer per batch plus one whole-branch debate review at the end (about 8-12 subagents)
- excluded: merge, marking the PR ready, rewriting history
Resume
Progress lives in the tracker. After each batch commit, mark its tasks done as spec-implement does; on re-invocation the closed entries are the done tasks. With no tracker, say at Start that a stopped run cannot resume and that spec-implement can continue it by hand.
Loop
Repeat until every task is done or the budget runs out.
- Select up to 5 tasks in
plan.jsonorder whosedepends_onare done or earlier in the same batch. - Implement each task in its own fresh subagent, one at a time, using code-subagents
Sequential mode and
references/implementor-prompt.md. Set OWNED_FILES from the task'sfiles. Select the agent per Delegation inatelier-orchestrator. Add these rules: do not stage, commit, push, or install anything the plan does not name; never add or editreview-decision:comments; never delete, skip, or weaken tests; return BLOCKED instead of asking a question. - Gate. Run code-subagents Batch Review as written. Validate each task's tests, the full suite, lint, and type check. Stop if anything fails twice (see "When Subagents Fail").
- Commit with code-commit once the diff has no out-of-scope paths and no added
review-decision:lines. Put the reviewer's Minor issues in the commit body. Then update the tracker. - Report one line, for example
Batch 2/5: T4, T7 done. Keep only condensed results in context. On BLOCKED,git stash pushthe blocked task's paths, give the stash ref in the report, and stop. Commit nothing from a partial batch.
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 · 92 lines · 66 tokens per session scan A aed084577361
spec-loop is a skill published in the GitHub repository martinffx/atelier (48 stars, last pushed 2d ago), licensed MIT. It adds 66 tokens to every session and 1,196 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-10-19.
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