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 hoavdc/CodexKit --skill codexkit-bug-huntgit clone --depth 1 https://github.com/hoavdc/CodexKitWrote 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/hoavdc/codexkit/codexkit-bug-hunt)<a href="https://agentmods.dev/skills/hoavdc/codexkit/codexkit-bug-hunt"><img src="https://agentmods.dev/badge/skills/hoavdc/codexkit/codexkit-bug-hunt/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/hoavdc/codexkit/codexkit-bug-hunt"><img src="https://agentmods.dev/badge/skills/hoavdc/codexkit/codexkit-bug-hunt.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 | $0.00027 | $0.00421 |
| Opus 5.5 | $0.00011 | $0.00168 |
| Sonnet 5.5 | $0.00005 | $0.00084 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
codexkit-bug-hunt 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.
What it actually says
Bug Hunt
Use this skill when a report says something is broken and you need disciplined debugging rather than guesswork.
Workflow
- Capture exact observed behavior and expected behavior.
- Reproduce with the cheapest reliable path.
- Narrow the failure boundary before editing code.
- Patch the smallest credible cause.
- Verify the original failure and nearby regressions.
Required outputs
- reproduction path
- root-cause hypothesis
- patch summary
- verification notes
Avoid
- fixing symptoms without a reproduction
- stacking unrelated cleanup into the bug fix
- claiming a root cause without evidence
Quality Criteria
- Every finding is tied to a specific evidence source (log, test, metric)
- Pass/fail criteria are binary and measurable — no subjective judgments
- Severity levels are assigned with clear thresholds
- Remediation steps are provided for all critical and high findings
Verification (4C)
| Check | Question |
|---|---|
| Correctness | Are all pass/fail criteria applied against the correct standard or rule? |
| Completeness | Were all required dimensions or checklist items evaluated? |
| Context-fit | Does the verification scope match the actual risk level of the deliverable? |
| Consequence | If this passed verification but had a hidden flaw, what is the worst-case impact? |
Edge Cases
- Incomplete data for full assessment — Document which checks were limited and flag for re-verification when data becomes available.
- Ambiguous pass/fail criteria — Request clarification from the standard owner before scoring. Mark as 'Needs Review'.
- Multiple overlapping standards — Identify the governing standard and note where others diverge.
Changelog
- v1.0.0 — Initial release
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 First seen · 58 lines · 27 tokens per session scan A 8bdbcc3de695
codexkit-bug-hunt is a skill published in the GitHub repository hoavdc/CodexKit (25 stars, last pushed 5d ago), licensed MIT. It adds 27 tokens to every session and 421 once invoked, about $0.0001 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.
Other skills, from other repositories
debug-hub
Evidence-first debugging WITH MCP tools. Use when debughub MCP server is available. Inject log calls, collect via HTTP API (port 39200), analyze through MCP tools, clean up when done. If debughub MCP is unavailable, use debug skill (bundled Python collector) instead.
checking-code-quality
Checks code quality metrics including complexity, duplication, naming conventions, and function length. Use when running quality gates, reviewing code smells, or checking lint rules. Automatically triggered on complex modules or post-refactor.
developing-software
Software development knowledge reference covering Python, Go, Rust, TypeScript, Java, C++, and Shell. Use when writing code, debugging, or following language-specific best practices.
indexing-code
Code relationship graph and temporal intelligence via abyss CLI. Provides caller tracing, impact analysis, hotspot detection, and file-level context gathering. Agent automatically runs abyss before modifying code to check impact. Works with any agent that has shell access.
Verification & Quality Assurance
Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
ha-self-diagnosis
Self-understanding and issue reporting for Hope Agent itself. Use when the user asks how Hope Agent works internally, asks about its own source code/docs/runtime behavior, reports a bug/failure/slowness/crash, asks to diagnose logs, or asks to create/submit a GitHub issue for a bug, feature request, or improvement…