Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add sequenzia/agent-alchemy/plugin install agent-alchemy-dev-toolsWrote 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/sequenzia/agent-alchemy/bug-killer)<a href="https://agentmods.dev/skills/sequenzia/agent-alchemy/bug-killer"><img src="https://agentmods.dev/badge/skills/sequenzia/agent-alchemy/bug-killer/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/sequenzia/agent-alchemy/bug-killer"><img src="https://agentmods.dev/badge/skills/sequenzia/agent-alchemy/bug-killer.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 | $0.00068 | $0.03719 |
| Opus 5.5 | $0.00027 | $0.01488 |
| Sonnet 5.5 | $0.00014 | $0.00744 |
| Haiku 4.5 | $0.00007 | $0.00372 |
Grade A, and why
bug-killer 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 — 471 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Bug Killer — Hypothesis-Driven Debugging Workflow
Execute a systematic debugging workflow that enforces investigation before fixes. Every bug gets a hypothesis journal, evidence gathering, and root cause confirmation before any code changes.
CRITICAL: Complete ALL 5 phases. The workflow is not complete until Phase 5: Wrap-up & Report is finished. After completing each phase, immediately proceed to the next phase without waiting for user prompts.
Phase Overview
- Triage & Reproduction — Understand, reproduce, route to quick or deep track
- Investigation — Gather evidence with language-specific techniques
- Root Cause Analysis — Confirm root cause through hypothesis testing
- Fix & Verify — Fix with proof, regression test, quality check
- Wrap-up & Report — Document trail, capture learnings
Phase 1: Triage & Reproduction
Goal: Understand the bug, reproduce it, and decide the investigation track.
1.1 Parse Context
Extract from $ARGUMENTS and conversation context:
- Bug description: What's failing? Error messages, symptoms
- Reproduction steps: How to trigger the bug (test command, user action, etc.)
- Environment: Language, framework, test runner, relevant config
- Prior attempts: Has the user already tried fixes? What didn't work?
- Deep flag: If
--deepis present, skip triage and go directly to deep track (jump to Phase 2 deep track)
1.2 Reproduce the Bug
Attempt to reproduce before investigating:
- If a failing test was mentioned, run it:
# Run the specific test to confirm the failure <test-runner> <test-file>::<test-name> - If an error was described, find and trigger it
- If neither, search for related test files and run them
Capture the exact error output — this is your primary evidence.
If the bug cannot be reproduced:
- Ask the user for more context via AskUserQuestion
- Check if it's environment-specific or intermittent
- Note "not yet reproduced" in the hypothesis journal
What ships with it
3 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 · 471 lines · 68 tokens per session scan A 8f868fba9fbe
bug-killer is a skill published in the GitHub repository sequenzia/agent-alchemy (45 stars, last pushed 4mo ago), licensed MIT. It adds 68 tokens to every session and 3,719 once invoked, about $0.0003 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
debugger
Systematic debugging method: 5-step root-cause analysis (capture, isolate, hypothesize, investigate, fix & verify) plus common bug-pattern reference. Use when errors, exceptions, test failures, or unexpected behavior appear. Loaded automatically by the debugger agent.
debug
Systematic bug investigation with a five-phase framework: reproduce, narrow, diagnose, fix, verify. Supports automated regression bisect via --regression flag. Produces a structured debug report with root cause analysis, regression test, and CQ/Q self-evaluations.
mcp-check
Validate MCP configuration and suggest improvements. Use when MCP servers fail to load, after editing .mcp.json, or when the user runs /mcp-check.
project-health-check
Audit project health across 7 dimensions (documentation, test coverage, security, code quality, dependencies, database, build/deploy) producing a scored report with prioritized fixes. Use for periodic checkups, before releases, or when the user runs /project-health-check.
ccc-systematic-debugging
Root-cause debugging under one law: no fix without a confirmed root cause. Reproduce, compare, hypothesize, then fix once with a failing test first. Use when investigating a bug, a failing or flaky test, or an error of unknown cause.
dekko-verify
Sanity-check a suspiciously low or zero call-graph result from dekko (getcallers, getcallees, findusages, impactedtests, unused) before concluding "no callers" or "dead code," or a heritage/throws-provenance result (query supertypes, query subtypes, query throws) that labels something (external) when you expect it to…