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 fw-ai/cookbook --skill debuggit clone --depth 1 https://github.com/fw-ai/cookbookWrote 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/fw-ai/cookbook/debug)<a href="https://agentmods.dev/skills/fw-ai/cookbook/debug"><img src="https://agentmods.dev/badge/skills/fw-ai/cookbook/debug/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/fw-ai/cookbook/debug"><img src="https://agentmods.dev/badge/skills/fw-ai/cookbook/debug.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 | $0.00080 | $0.00759 |
| Opus 5.5 | $0.00032 | $0.00304 |
| Sonnet 5.5 | $0.00016 | $0.00152 |
| Haiku 4.5 | $0.00008 | $0.00076 |
Grade A, and why
debug 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 today.
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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug
Debug: triage a stuck or failed Fireworks training run.
Debug is read-only by default. Do not create jobs, upload data, or spend without
an explicit handoff to configure and a new approved plan.
Entry routing
| Signal | Route |
|---|---|
| New training or approved retry | configure |
| Unclear method, data, or starting example | research |
| Failure, stall, bad quality, resume, or serving issue | stay in debug |
Research owns the welcome-entry question and its privacy notice. Route a
vague first message there instead of asking a second welcome question.
Attribution and privacy
Reuse the run's FIREWORKS_SESSION_ID. If none exists, create one UUID. Set:
export FIREWORKS_CLIENT_SOURCE="fireworks-training-skill/2.2.0"
Record entry_skill: debug in the private run manifest. Before the first
structured question, show
../fireworks-training/references/telemetry-notice.md.
Check firectl skill-journey record --help once. When available, record only
registered IDs through ../fireworks-training/references/telemetry.md. If it is
unavailable or the user opts out, keep local run state and continue.
Never send raw errors, customer prose, credentials, datasets, or paths as journey telemetry.
Triage
- Read
references/triage-paths.md. - Ask one category question: job state, error, quality, resume/checkpoint, or deploy/serving.
- Stop and wait for the answer.
- Follow the ordered read-only checks for that category.
- Use the detailed carrier references listed below.
Three-strike rule
After three failed hypotheses on the same issue:
- Stop guessing.
- Build an escalation bundle with UTC timestamps, resource IDs, model and shape, CLI and SDK versions, cookbook commit, retry history, evidence, and what was ruled out.
- Redact credentials and customer data.
- State what the evidence supports and what remains unknown.
Handoff
- Route to
configureonly when the user wants a new or retry run. - Route to
researchwhen the starting example or method is wrong. - On resolution without new spend, record
debug_resolvedand stop.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- today Changed · +1 lines · +7 tokens per session 125e9293f84d
- 1mo ago First seen · 90 lines · 73 tokens per session scan A a739ed162c8e
debug is a skill published in the GitHub repository fw-ai/cookbook (223 stars, last pushed today), licensed Apache-2.0. It adds 80 tokens to every session and 759 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 2026-09-09.
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rocketride-debugging-pipelines
Use when a RocketRide pipeline run failed, errored, or produced wrong/empty output, and you need to find the failing node and fix it. Reads run status and execution traces, diagnoses the cause, and routes back to design or configuration. Also use directly when asked to debug a run.
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ai-engineer
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embedding-architect
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