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 ronronner02/codepilot-agent --skill spec-debuggit clone --depth 1 https://github.com/ronronner02/codepilot-agentWrote 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/ronronner02/codepilot-agent/spec-debug)<a href="https://agentmods.dev/skills/ronronner02/codepilot-agent/spec-debug"><img src="https://agentmods.dev/badge/skills/ronronner02/codepilot-agent/spec-debug/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/ronronner02/codepilot-agent/spec-debug"><img src="https://agentmods.dev/badge/skills/ronronner02/codepilot-agent/spec-debug.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 | $0.00044 | $0.08273 |
| Opus 5.5 | $0.00018 | $0.03309 |
| Sonnet 5.5 | $0.00009 | $0.01655 |
| Haiku 4.5 | $0.00004 | $0.00827 |
Grade A, and why
spec-debug 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 — 394 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Debug and Fix
Find root causes, then fix them. This skill investigates bugs systematically — tracing the full causal chain before proposing a fix — and optionally implements the fix with test-first discipline.
Workflow Contract Summary
- 输入： 可复现的失败、错误、回归、stack trace、issue 或明确异常行为。
- 输出： 证据闭合的 causal chain、最小修复、回归验证与结构化 handoff；若未授权修复则只返回诊断。
- 硬出口： 无法复现且缺 replacement evidence、因果链仍有未验证跳步、target repo/source owner/dirty overlap 未解决，或 required verification 失败时不得声明 root cause/fix complete。
- 权威： 运行时复现、source、test 与 log 提供事实；LLM 判断因果充分性；诊断、local mutation、commit 与 landing 分别授权。
- 消费者： 用户、
spec-work、spec-code-review、issue/PR owner 与后续知识沉淀流程。
<bug_description> # </bug_description>
Mode
The default mode is interactive. Investigate, present the causal chain, and use the Phase 2 fix-choice gate and Phase 4 handoff as written below.
When the invocation includes mode:pipeline-return, strip that token from
<bug_description> and load references/pipeline-return.md. This mode is for
an outer workflow such as spec-lfg: it replaces blocking questions with
conservative defaults, applies only an inherited and explicitly authorized
local convergent fix, and returns a structured envelope to the caller. The
mode token does not authorize mutation, commit, push, external communication,
credentials, or tracker writes.
Scenario Capability
Follows docs/contracts/workflows/scenario-capability-matrix.md.
Overrides: high-risk
foreign-residual-workspace->blocked-action-required: stop before fix mutation, root-cause-confirmed claims that depend on suspect local artifacts, commits, or PR-ready handoff until the named cleanup/init action runs or the user explicitly accepts degraded evidence.- optional external-tool evidence unavailable ->
fallback-only: continue with bounded direct source, test, log, runtime-probe, and user-provided evidence; disclose the missing capability and do not extend root-cause or blast-radius claims beyond that evidence. non-git-build-workspacecoverage gaps ->partial: keep investigation/fixes inside the explicittarget_repoor inspected build surface and directly inspect uncovered modules before claiming they are unaffected.
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 · 394 lines · 44 tokens per session scan A b72184a8b9e6
spec-debug is a skill published in the GitHub repository ronronner02/codepilot-agent (0 stars, last pushed 1mo ago), licensed MIT. It adds 44 tokens to every session and 8,273 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 2026-08-31.
Other skills, from other repositories
trace
Use when encountering bugs, test failures, runtime errors, broken builds, or "this doesn't work" reports. Systematic root-cause analysis before any patch — never blind-patches symptoms. Standalone, ends with a final-integration review of the fix. Trigger with /hyperflow:trace, "debug this", "find the root cause", "why…
oma-debug
Diagnose a reproducible failure, fix its cause, and verify the regression. Use for crashes, incorrect behavior, and failing tests.
error-analysis
Evals-first error analysis for LLM apps: clusters real Langfuse or JSONL traces into a human-confirmed failure taxonomy with counts, then recommends binary pass/fail evals for recurring named modes. Use to learn what to measure before writing evals. Not for CI failures.
paired-probe
Refuse a verdict a probe did not earn. Runs a check where the fault IS present and where it is NOT, and blocks the answer when both arms print the same thing, because a check that cannot disagree with you has measured nothing. Also catches the zero-sample sweep that reads as "clean" and the swallowed error that reads…
compiler-11897630
A coverage skill that marks or reports how much of a set of instructions is covered by tests. Test coverage is a measure of which code paths tests exercise.
dawn
Build AI agents and workflows with the Dawn framework — the TypeScript meta-framework for LangGraph. Use when creating, editing, or debugging a Dawn app (routes, tools, state, agents, workflows, testing, deployment).