forge-debug

A systematic debugging playbook for investigating bugs, crashes, failing tests, regressions, and flaky tests.

In plain words
What is it for?
Use it to reproduce a failure, isolate its cause, create a fix, add a regression test, and verify the complete change.
Why use it?
It prevents guessed fixes by requiring the cause to be investigated and the result to be proven with a regression test, a test that catches the same problem in the future.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/forgeyclap/claude-forge/forge-debug
Any agent
npx skills add ForgeyClap/claude-forge --skill forge-debug
Clone the repo
git clone --depth 1 https://github.com/ForgeyClap/claude-forge

Made for: Claude Code, Codex.

Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 955 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00042 $0.00955
Opus 5 $0.00021 $0.00477
Sonnet 5 $0.00008 $0.00191
Haiku 4.5 $0.00004 $0.00096

Measured 2d ago against content hash 8571c36e6f9d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

forge-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 2d 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.

.claude/skills/forge-debug/SKILL.md · 60 lines

How it starts

The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Forge playbook — Systematic debugging

Do not duplicate ECC skills — defer to: systematic-debugging (the deep methodology reference). This file is the Forge-specific orchestration wrapper: it binds that methodology to the honesty core and to which Boss does what.

Hard rules

  • The Iron Law: no fix without root-cause investigation first. A patch that only makes the symptom go away, without an explanation of why the bug happened, is not a fix — it is a guess.
  • Never claim "fixed" without proof. Per the project honesty core (CLAUDE.md → Honesty), a bug is only "fixed" when there is a real regression test that failed before the change (RED) and passes after it (GREEN). A verbal claim of "should be fixed now" is not evidence.
  • Do not silently patch around a failure (swallowed exception, widened try/catch, disabled test, loosened assertion) to make a check go green — that is a rework-flag, not a fix.
  • If root cause can't be found within a reasonable number of attempts, say so honestly (BLOCKED / needs owner input) rather than shipping a guess dressed up as a fix.

The loop (reproduce → isolate → root-cause → fix → regression test → verify)

  1. Reproduce. Get a minimal, reliable repro (exact command, exact input, exact error). If it can't be reproduced, that itself is a finding — don't invent a story around a bug you haven't actually seen.
  2. Isolate (bisect / binary-search). Narrow the surface: which commit introduced it (git bisect), which input triggers it (binary-search the input space), which layer owns it (add targeted logging / breakpoints, remove code paths until the symptom disappears). Prefer removing variables over adding theories.
  3. Root-cause, not symptom. State the mechanism in one sentence: "X happens because Y does Z under condition W." If you can't state it that precisely, you don't have the root cause yet — keep isolating.
  4. Fix at the root, matching the existing architecture and conventions (see coding-style.md) — not a parallel workaround bolted on beside the real cause.
  5. Regression test. Write a test that fails on the pre-fix code and passes on the post-fix code. It stays in the suite permanently — it is the proof, and it prevents the same bug returning silently.
  6. Verify. Re-run the full relevant suite (not just the new test) to confirm no other case regressed; quote the real command and its real output.

Read the full file on GitHub · 60 lines

Changes

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.

  1. 2d ago First seen · 60 lines · 42 tokens per session scan A 8571c36e6f9d

Subscribe to this mod's changes

forge-debug is a skill published in the GitHub repository ForgeyClap/claude-forge (2 stars, last pushed 29d ago), licensed MIT. It adds 42 tokens to every session and 955 once invoked, about $0.0002 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 2026-08-31.

Related

Other skills, from other repositories

batch

Execute batch operations on multiple files in parallel. Automatically discovers files, splits into chunks, and processes with parallel worker agents. Use /batch followed by operation and file pattern.

QwenLM/qwen-code · 37 tokens

extension-creator

Create, scaffold, customize, validate, and locally test Qwen Code extensions. Use when the user wants a new Qwen Code extension, needs help choosing an extension template, wants to add QWEN.md context, commands, skills, agents, MCP servers, settings, hooks, channels, or LSP servers, or asks how to link and test an…

QwenLM/qwen-code · 96 tokens

notion

Notion API for creating and managing pages, databases, and blocks. Use when the user wants to create a Notion page, query a Notion database, update Notion properties, search Notion, add content to Notion, manage Notion blocks, or interact with Notion data sources and workspaces via the API.

elizaOS/eliza · 69 tokens

pr-feedback

Fetches PR review feedback and inline comments, categorizes them, and presents options to the user. Use when the user asks to get, read, address, or fix review comments on a pull request.

strands-agents/harness-sdk · 44 tokens

dev-pain-finder

Scrape real developer pain points for any keyword, technology, or problem space from Reddit, Hacker News, dev.to, and GitHub Discussions simultaneously — then group complaints by theme, score them by frequency and upvote weight, and return a ranked opportunity map showing where developer frustration is high and…

tinyfish-io/tinyfish-cookbook · 160 tokens

argent-native-profiler

Native profiling for CPU hotspots, UI hangs, memory issues. iOS via xctrace; Android via Perfetto. Use when diagnosing native-level performance issues.

software-mansion/argent · 37 tokens