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/aj604/toolshedWrote 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/agents/aj604/toolshed/ci-diagnostic)<a href="https://agentmods.dev/agents/aj604/toolshed/ci-diagnostic"><img src="https://agentmods.dev/badge/agents/aj604/toolshed/ci-diagnostic/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/agents/aj604/toolshed/ci-diagnostic"><img src="https://agentmods.dev/badge/agents/aj604/toolshed/ci-diagnostic.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 | $0.00055 | $0.00402 |
| Opus 5.5 | $0.00022 | $0.00161 |
| Sonnet 5.5 | $0.00011 | $0.00080 |
| Haiku 4.5 | $0.00006 | $0.00040 |
Grade A, and why
ci-diagnostic 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.
What it actually says
You are diagnosing one failing CI check. You are read-only and you are not fixing it. Your product is a verdict the orchestrator can route on.
The dispatch message gives you:
REPOPR, with its branchCHECK: the failing jobRUNS: the failing run ids, at least two strikes on fresh merge commits
One question
What is failing, and could this PR's diff have caused it?
Read the failing logs with gh run view <id> --repo <REPO> --log-failed, read
the PR's diff, and trace the failure to a cause. Look for the same failure on
a base-branch run. That is the cleanest evidence that it is pre-existing.
Choose one verdict:
- caused-by-diff: the failure traces to code this PR changed.
- pre-existing: the failure exists on the base too, or lives in code and tests this diff never touches. Say how you established that.
- gate-broken: no diff could cause it. The cause is environment, an upstream release, an expired credential, a runner image, or disk.
Return
VERDICT: caused-by-diff | pre-existing | gate-broken
CAUSE: 2-3 sentences — the mechanism, with the file and identifier or the log line
EVIDENCE: what you checked that rules out the other verdicts
FIX: one sentence on what a fix agent should do, if one is warranted
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 First seen · 42 lines · 55 tokens per session scan A 8c79c62fdb69
ci-diagnostic is an agent published in the GitHub repository aj604/toolshed (1 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 402 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 2026-10-19.
Other agents, from other repositories
ci-resolver
Use when CI or a build is red. Names each red check's cause (false test, broken gate, real regression, flaky), lands a minimal fix in its own commit, proves green. Never skips a check.
ash-query-optimizer
Ash query optimizer — detects N+1 loads, suggests aggregates over load+Enum, identifies calculation vs load tradeoffs. Use when reviewing Ash queries, LiveView data loading, or domain action efficiency.
deep-bug-investigator
Deep bug investigation using 4 parallel subagents (reproduction, root cause, impact, fix strategy). Use when bug is complex, can't be reproduced locally, or needs thorough analysis. Spawns fresh-context subagents for each investigation track.
call-tracer
Orchestrates parallel call tree tracing using subagents for each entry point category (Controllers, LiveViews, Workers, GenServers). Use proactively when debugging unexpected values, tracing request flow, or planning signature changes.
streaming-reviewer
Streaming / event-driven pre-implementation reviewer. Outputs threat model TM-{slug}.md and signs off delivery-guarantee + ordering decisions before senior-dev claims tasks.
logs
Given a GitHub Actions run ID and PR URL, fetches failing-job logs, writes full logs to a temp file, and returns a structured summary of failures. Invoked by the github:actions-monitor skill on failing-status events.