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 adrianco/retort --skill diagnose-failed-rungit clone --depth 1 https://github.com/adrianco/retortWrote 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/adrianco/retort/diagnose-failed-run)<a href="https://agentmods.dev/skills/adrianco/retort/diagnose-failed-run"><img src="https://agentmods.dev/badge/skills/adrianco/retort/diagnose-failed-run/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/adrianco/retort/diagnose-failed-run"><img src="https://agentmods.dev/badge/skills/adrianco/retort/diagnose-failed-run.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 | $0.00109 | $0.01768 |
| Opus 5 | $0.00055 | $0.00884 |
| Sonnet 5 | $0.00022 | $0.00354 |
| Haiku 4.5 | $0.00011 | $0.00177 |
Grade A, and why
diagnose-failed-run 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.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Diagnose a Failed Retort Run
Overview
A run failing the mechanical gate (test_coverage=0 → all metrics zeroed → status=failed)
says only that the tests didn't run/pass under the scorer — not that the model
produced bad code. Historically most "failures" in this repo were harness/measurement
artifacts, not model defects. This skill is the judgment layer on top of retort diagnose:
it establishes the real cause with direct evidence before anyone attributes, reports,
or gates on it.
It exists because we repeatedly drew wrong conclusions by inferring from a signature ("flaky", "concurrency", a wrong env var, a wrong tool-permission fix) that end-to-end checks later overturned. The cost of guessing here is hours and bad decisions.
Cardinal rules
- Ground-truth before concluding. Run the tests yourself, inspect the workspace, read the agent logs. Never attribute a cause from the gate verdict, a duration, or a single log line alone.
- Label every claim
[DIRECT](observed: command output, file state, a reproduced result) vs[HYPOTHESIS](inferred, not yet tested). Don't ship a hypothesis as a cause. If a cause is unconfirmed, say so and name the experiment that would confirm it. - Read the DB and the agent logs. The recorded scores/session show which tool or
step failed; the agent stderr shows why (the permission type, the error). You usually
need both — e.g. the session said "read rejected", but only
--print-logsstderr revealed the real permission wasexternal_directory. - Verify any fix end-to-end (through the harness), not just CLI/unit. A fix that passes a CLI probe can still fail in the runner (a wrong env var passed both).
Inputs in each runs/<cell>/repN/
| File | Use |
|---|---|
TASK.md |
What the agent was asked to build |
stack.json |
language / agent / model / tooling for this cell |
scores.json |
recorded metrics (all 0 ⇒ gate-failed) |
| generated source | what the agent actually produced — check it exists and where (subdirs/packages count) |
_agent_stdout.log |
the agent's full --format json / --mode json event stream (tool calls + their status, errors, the final text) |
_agent_stderr.log |
the agent's internal logs (permission evaluations, hangs, provider errors) — for opencode, requires --print-logs |
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 · 115 lines · 109 tokens per session scan A 20016484ed1f
diagnose-failed-run is a skill published in the GitHub repository adrianco/retort (203 stars, last pushed today), licensed Apache-2.0. It adds 109 tokens to every session and 1,768 once invoked, about $0.0005 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.
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