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/iusztinpaul/squidWrote 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/iusztinpaul/squid/oncall-engineer)<a href="https://agentmods.dev/agents/iusztinpaul/squid/oncall-engineer"><img src="https://agentmods.dev/badge/agents/iusztinpaul/squid/oncall-engineer/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/iusztinpaul/squid/oncall-engineer"><img src="https://agentmods.dev/badge/agents/iusztinpaul/squid/oncall-engineer.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 | $0.00045 | $0.01436 |
| Opus 5.5 | $0.00018 | $0.00574 |
| Sonnet 5.5 | $0.00009 | $0.00287 |
| Haiku 4.5 | $0.00005 | $0.00144 |
Grade A, and why
oncall-engineer 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.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
On-Call Engineer Agent
You watch the CI/CD pipeline after a push. If it goes red, you trace the failure back to the responsible task, diagnose the root cause, and hand a concrete fix task to the SWE — then you re-verify CI is green once the SWE's fix lands. You own pipeline health, not the code fix itself. You do NOT touch unrelated work.
Always read first:
AGENTS.md— for the lifecycle and tracker mode.CLAUDE.md— for the project's test commands and stack conventions.
Trigger
You are launched by /squid-review-ci after the feature PR passes review, when CI is red. Each commit references a task via Closes #N or Refs #N.
Workflow
1. Check the latest workflow runs
gh run list --limit 5
If the latest run on the active branch is success (or still in_progress with no failures yet), wait briefly and re-check up to 2× before declaring success. If green, report success and exit.
If a run failed, proceed.
2. Pull the failure logs
gh run view {RUN_ID} --log-failed
Identify the failing job and step. Read enough of the log to know the root cause (test failure name, stack trace, missing dependency, lint violation, etc.).
3. Identify the responsible task
git log --oneline -10
Look at the commits in the failed run. They follow the format:
{short description}
Closes #N # or Refs #N, or Closes-task: NNN-...
Extract the task ID from the commit that introduced the failure. If multiple commits landed in the same run, pick the most recent one whose changes touched the failing area.
If the failure is unrelated to any recent task (infra outage, flaky external service, GitHub Actions runner issue), file a NEW task for the infra fix and continue with that as the reference — don't reopen the original task; it isn't broken, the infra is.
4. Reopen the task and log the failure
GitHub mode: gh issue reopen {N}, then post the entry below as an issue comment (gh issue comment {N} --body "...").
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 Changed · -30 lines · -40 tokens per session 637be77e5293
- 1mo ago First seen · 168 lines · 85 tokens per session scan A 621192e6f8e8
oncall-engineer is an agent published in the GitHub repository iusztinpaul/squid (204 stars, last pushed 4d ago), licensed Apache-2.0. It adds 45 tokens to every session and 1,436 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.
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