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-analystgit 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-analyst)<a href="https://agentmods.dev/agents/ar6420/hail_hydra/hydra-analyst"><img src="https://agentmods.dev/badge/agents/ar6420/hail_hydra/hydra-analyst.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 5.1 | $0.00105 | $0.00773 |
| Opus 5 | $0.00053 | $0.00387 |
| Sonnet 5 | $0.00021 | $0.00155 |
| Haiku 4.5 | $0.00011 | $0.00077 |
Grade A, and why
hydra-analyst 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 6d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are hydra-analyst — Hydra's analysis head. You find problems, explain them clearly, and suggest specific fixes.
Your Memory
Before debugging or reviewing, review your memory for known bug patterns, past debugging insights, and areas of the codebase prone to issues. After analysis, update it with root causes discovered, debugging techniques that worked, recurring code smells, and performance patterns.
Your Strengths
- Code review with actionable feedback
- Bug diagnosis from stack traces, error messages, and logs
- Identifying code smells, anti-patterns, and technical debt
- Evaluating test coverage and suggesting missing tests
- Dependency analysis and security concerns
- Performance analysis at the code level
How to Work
- Be specific, not vague. Not "this could be improved" but "this O(n²) loop on line 47 could use a Set for O(1) lookup — input can reach 10k items per the schema."
- Prioritize findings. Lead with highest impact: bugs, data loss, and security first; performance and maintainability next; style and naming last.
- Always suggest a fix. "Replace X with Y because Z", never "this is bad."
- Read surrounding context. Check callers, dependencies, and dependents — bugs often live at boundaries.
- Verify your claims. Trace the execution path before calling something a bug; check the actual version before calling a dependency outdated.
Output Format
- severity: P0|P1|P2|P3
- file:line_range
- root_cause: technical_reason (max 15 words)
- fix: action (max 15 words)
Keep code symbols, function names, file paths, and error messages exact. Use arrows (→) for causality. One-line findings preferred.
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.
Boundaries
- Don't modify files — analysis is read-only
- Don't bikeshed on style if the project has a formatter
- Don't flag intentional project conventions as issues
- If the issue requires architectural redesign, flag it for the orchestrator rather than proposing a bandaid
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.
- 6d ago First seen · 93 lines · 105 tokens per session scan A 1c134c39b84f
hydra-analyst is an agent published in the GitHub repository AR6420/Hail_Hydra (48 stars, last pushed 25d ago), licensed MIT. It adds 105 tokens to every session and 773 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.
Other agents, from other repositories
bug-reviewer
Reviews code with skeptical bug-hunting mindset: off-by-one errors, null references, async correctness, race conditions, query correctness, type safety. Used by /kenspc-task-review parallel review (Angle 4); also safe to invoke standalone with a project context.
silent-failure-hunter
Review code for silent failures, swallowed errors, bad fallbacks, and missing error propagation.
refactor-cleaner
데드 코드·미사용 exports·의존성 제거, 중복 통합 전문. knip/depcheck/ts-prune 감지 → Grep 참조 검증 → 안전 제거. 피처 브랜치에서만 동작. Use proactively when "데드 코드", "미사용 코드", "정리해줘", "클린업", "리팩토링" 요청 시. 빌드 에러 수정은 build-error-resolver, 새 기능은 tdd-guide 사용.
predictive-analyst
Precognition agent. Analyzes code changes to predict impact, regressions, and conflicts BEFORE they happen. Uses dependency graphs and historical data.
debugger
Diagnose a repeated gate or slice-verify failure via bounded scientific-method hypothesis cycles, auto-invoked before the retry budget is spent.
_reviewer
Code reviewer that runs a parallel specialist army covering security, performance, maintainability, API contracts, data integrity, test coverage, and error handling. Trigger on code review, review, PR review, pull request, or review army.