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 escoffier-labs/brigade --skill refiregit clone --depth 1 https://github.com/escoffier-labs/brigadeWrote 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/escoffier-labs/brigade/refire)<a href="https://agentmods.dev/skills/escoffier-labs/brigade/refire"><img src="https://agentmods.dev/badge/skills/escoffier-labs/brigade/refire/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/escoffier-labs/brigade/refire"><img src="https://agentmods.dev/badge/skills/escoffier-labs/brigade/refire.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00057 | $0.01158 |
| Opus 5.5 | $0.00023 | $0.00463 |
| Sonnet 5.5 | $0.00011 | $0.00232 |
| Haiku 4.5 | $0.00006 | $0.00116 |
Grade A, and why
refire 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- refire — 98% identical, 25 lines differ
How it starts
The opening of the file, as written. The whole thing — 57 lines — stays where its author put it; the contents beside it link to each section on GitHub.
refire
A plate comes back to the kitchen. The line's instinct is to fire the same dish again, faster; the chef's job is to find out why it came back first, because a refire of the same mistake comes back twice and now the diner is angrier. This skill is the chef's version of debugging: no fix until the cause of the sendback is known.
Core principle: no fixes without root cause first. A fix that makes the symptom disappear without explaining it is not a fix, it is a scheduled second incident. Violating the letter of this process is violating its spirit.
Find out why it came back
Before any fix, in order:
- Read the error, all of it. The full traceback, the line numbers, the actual message. It frequently names the cause outright.
- Reproduce it. Trigger it reliably with the smallest input you can. Cannot reproduce? Gather more evidence; do not guess.
- Check what changed.
git logandgit diffaround when it broke: recent commits, new dependencies, config or environment drift. Most bugs are young. - Check the documented contract. Schema docs, interface comments, the spec. The difference between the documented behavior and the actual behavior usually points straight at the cause, and the fix must satisfy the contract, not just the failing test.
- Trace to the source. Where does the bad value originate? Who called this with it? Walk up the stack until the origin; the fix lands there, not at the crash site. In a multi-component system, instrument each boundary (what enters, what exits) and run once to see which layer breaks, rather than theorizing across all of them.
- Compare against what works. Find the nearest working sibling (same pattern, same codebase) and list every difference, including the ones that "can't matter".
Then fix it, once
- State the hypothesis. "X is the root cause because Y", written, specific. If you cannot finish that sentence, return to investigation; do not pretend.
- Pin it with a failing test first. The test reproduces the bug and asserts the violated contract, not just the absence of the crash. This is taste's loop applied to a bug; a fix without a test that failed is a fix that cannot prove itself and a regression nobody will catch.
- One minimal change. Test the hypothesis with the smallest change that fixes the cause. One variable. No bundled cleanups, no "while I'm here".
- Verify and read the output. The pinned test passes, the whole suite stays green, the original symptom is actually gone.
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.
- 1mo ago First seen · 57 lines · 57 tokens per session scan A f800ce970aff
refire is a skill published in the GitHub repository escoffier-labs/brigade (81 stars, last pushed today), licensed MIT. It adds 57 tokens to every session and 1,158 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
slm-graph
Index and query a codebase as a structural graph — build the code graph, trace blast radius of a change, find callers/callees/inheritors, semantic code search by meaning, assemble PR review context, and detect what changed since last index. Use when the user asks how code connects, what breaks if X changes, what calls…
tracelet-instrument
Instrument an AI agent or LLM app with OpenTelemetry and watch its runs live in tracelet (local DevTools). Use when asked to add tracing/observability to an agent, or to debug what an agent actually did.
cvm-ai-doctor
A health-diagnosis workflow for servers, computers, virtual machines, and containers on Linux, macOS, or Windows.
pre-action-interceptors
Use when a tool error begins with "INTERCEPTOR:", a sent message was silently hedged or rewritten, or the user asks about active guards or blocked actions. Not for ordinary tool errors.
observability
Periodic health sweep of the running system via the debug pipeline (cloud logs / k8s / daemon / DB slices). On a real anomaly, open a bug task (--kind workitem) carrying the evidence refs so it re-enters the bugfix loop. A healthy sweep opens NO task — never fabricate a bug.
prismer-python-debugpy
Debug Python: pdb REPL + debugpy remote (DAP).