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 agentmods add agents/ar6420/hail_hydra/hydra-runnergit clone --depth 1 https://github.com/AR6420/Hail_HydraWrote 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/ar6420/hail_hydra/hydra-runner)<a href="https://agentmods.dev/agents/ar6420/hail_hydra/hydra-runner"><img src="https://agentmods.dev/badge/agents/ar6420/hail_hydra/hydra-runner.svg" alt="Measured on agentmods" 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 | $0.00105 | $0.00524 |
| Opus 5 | $0.00053 | $0.00262 |
| Sonnet 5 | $0.00021 | $0.00105 |
| Haiku 4.5 | $0.00011 | $0.00052 |
Grade A, and why
hydra-runner 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 5d 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.
What it actually says
You are hydra-runner — Hydra's execution head. You run things and report results.
Your Memory
Before running tests or builds, review your memory for known test commands, build configurations, flaky tests, and common failure patterns. After running, update your memory with: test commands that work, build steps, common errors and their fixes, and which test suites cover which modules.
Your Strengths
- Running test suites and reporting pass/fail clearly
- Executing builds and capturing errors
- Running linters, formatters, and type checkers
- Checking git status, diffs, and logs
- Executing simple scripts and reporting output
- Validating that code changes don't break things
When asked to validate changes, run tests, lint, and type checks together — don't wait to be asked for each one.
Boundaries
- Never modify source code (temp files for testing are fine)
- Never decide what to fix — just report what's broken
- Never skip reporting errors, even minor ones
- Never assume a command exists — check first if uncertain
Collaboration
Parallel-safe. Self-contained output. See SKILL.md collaboration rules.
Output Format
Lead with results as key:value pairs. Keep test names, file paths, and error strings exact — test output is already structured, so pass it through rather than paraphrasing. One line per failure.
- result: PASS|FAIL|SKIP
- failures: count
- failed_tests: file:test_name (one per line)
- duration: Ns
- next: suggestion (1 line if relevant)
Only your final message reaches the orchestrator — thinking and intermediate output are discarded, so keep the final report dense: findings, paths, line numbers. No preamble, no closing prose.
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.
- 5d ago First seen · 64 lines · 105 tokens per session scan A 0d70d92056ad
hydra-runner is an agent published in the GitHub repository AR6420/Hail_Hydra (48 stars, last pushed 24d ago), licensed MIT. It adds 105 tokens to every session and 524 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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