Agent skill

Production Error Hunt

by different-ai in different-ai/openwork

Traces an opaque production error in an OpenWork build to its cause using local server logs and Sentry, names the regressing PR and files a report.

Custom licenceAuto-check passedDevelopment

Install Production Error Hunt

skills CLI
$ npx skills add different-ai/openwork --skill hunt-a-prod-error -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install different-ai/openwork hunt-a-prod-error --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/different-ai/openwork.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.opencode/skills/hunt-a-prod-error .claude/skills/hunt-a-prod-error && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
hunt-a-prod-error
GitHub stars
24k
Token cost
~803 tokens
SKILL.md length
347 words
Files
1
Skills in repo
33
Repo updated
First seen
Licence
Custom licence

At a glance

Traces an opaque production error in an OpenWork build to its cause using local server logs and Sentry, names the regressing PR and files a report.

  • Works in 5 steps: Local logs: where and how often → Sentry: what threw → Name the regression → …
  • A user reports internal_error, a 500 or Unexpected server error in a shipped build
  • SKILL.md covers 1. Local logs: where and how…, 2. Sentry: what threw, 3. Name the regression and 4. Reproduce on the shipping…, plus 1 more section
  • Calls rg, python3 and npx; reaches us.sentry.io

What it does

An opaque error has two halves, and the skill insists on both. Local logs say where and how often: the desktop server log (OTLP JSON, one record per request) and the engine log, with 5xx responses tallied by route and compared with sibling routes that did not fail. Sentry says what threw: the agent searches issues through OpenWork Connect, filters by `surface:server`, the templated `route` and `release`, and reads the stack, first-seen time, users and event count.

Next it correlates the first-seen time with recent git history on the files in the stack, confirms the shipped code matches source, and reproduces the mechanism on the runtime where the error happened, since a repro on a different runtime proves nothing. Finally it files an issue in Linear with the user-facing string, route tally, Sentry issue IDs, mechanism, repro, regressing PR and a proposed fix, and replies where the report came from. One caveat noted is that proxy catch blocks send the real exception only to Sentry.

When your agent uses it

  • A user reports internal_error, a 500 or Unexpected server error in a shipped build
  • Matching a Sentry issue to the pull request that introduced it
  • Tallying 5xx errors by route in server logs

Example prompts

  • “A user hit Unexpected server error in the desktop app, so find the cause and file it.”
  • “Tally 5xx by route in the OpenWork server log and compare against the routes that worked.”
  • “Which PR introduced the new Sentry issue on the workspace opencode route?”

Requirements

  • Access to OpenWork's local server and engine logs
  • Sentry connected through OpenWork Connect
  • A Linear workspace for filing the issue

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Local logs: where and how often
  2. Sentry: what threw
  3. Name the regression
  4. Reproduce on the shipping runtime
  5. File and reply

What it can do on your machine

Read from SKILL.md and the folder at commit 9ce20f8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • rg
    • python3
    • npx
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • us.sentry.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Production Error Hunt loads about 803 tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 347 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~803

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 347 words (~803 tokens).

“An opaque error has two halves. Local logs say where (route, status, timing, burst shape). Sentry says what (the exception and stack). You need both before naming a cause; either alone produces a guess.”

— opening of SKILL.md by different-ai, Custom licence
name
hunt-a-prod-error

Read the full SKILL.md on GitHub

Files

Just SKILL.md in .opencode/skills/hunt-a-prod-error of different-ai/openwork.

Open the folder on GitHubat commit 9ce20f8

Compare with similar skills

Production Error Hunt next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Production Error Hunt compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Production Error Hunt this skilldifferent-ai/openwork24k—~803Automated safety check: PassCustom licence
Axiom SRE Investigatoropenclaw/clawhub9.5k—~7.1kAutomated safety check: PassMIT
Code Design Rationale Investigatorcursor/plugins10k9 repos~2.6kAutomated safety check: PassNone
Debug MasteryxenitV1/claude-code-maestro229—~2.5kAutomated safety check: NotesMIT
Debugging and Error Recoveryaddyosmani/agent-skills103k1 repos~2.6kAutomated safety check: PassMIT
Sentry Issue Fix Looptixl3d/tixl5.1k—~2.1kAutomated safety check: NotesMIT

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Works with

Questions about Production Error Hunt

What does Production Error Hunt do?

Traces an opaque production error in an OpenWork build to its cause using local server logs and Sentry, names the regressing PR and files a report. An opaque error has two halves, and the skill insists on both. Local logs say where and how often: the desktop server log (OTLP JSON, one record per request) and the engine log, with 5xx responses tallied by route and compared with sibling routes that did not fail.

When should I use Production Error Hunt?

Production Error Hunt fits situations like: A user reports internal_error, a 500 or Unexpected server error in a shipped build; matching a Sentry issue to the pull request that introduced it; tallying 5xx errors by route in server logs.

How do I install Production Error Hunt in Claude Code?

Run `npx skills add different-ai/openwork --skill hunt-a-prod-error -a claude-code`. Or copy the skill folder (.opencode/skills/hunt-a-prod-error in different-ai/openwork) into .claude/skills/hunt-a-prod-error in your project. Claude Code loads it when a task matches its description.

How do I install Production Error Hunt in Codex?

Run `npx skills add different-ai/openwork --skill hunt-a-prod-error -a codex`. Or copy the skill folder (.opencode/skills/hunt-a-prod-error in different-ai/openwork) into .agents/skills/hunt-a-prod-error in your project. Codex loads it when a task matches its description.

Can I use Production Error Hunt in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add different-ai/openwork --skill hunt-a-prod-error -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hunt-a-prod-error, .gemini/skills/hunt-a-prod-error, .github/skills/hunt-a-prod-error and .opencode/skills/hunt-a-prod-error in your project.

What does Production Error Hunt need to run?

Going by SKILL.md and its folder, Production Error Hunt needs the command-line tools its instructions call (rg, python3, npx and git). Our summary lists: Access to OpenWork's local server and engine logs; Sentry connected through OpenWork Connect; A Linear workspace for filing the issue.

Does Production Error Hunt access the network?

SKILL.md names 1 domain. In commands or code: us.sentry.io; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Production Error Hunt safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Production Error Hunt use?

Production Error Hunt has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.

How many tokens does Production Error Hunt use?

About 803 tokens (SKILL.md is roughly 3.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Production Error Hunt?

Skills that share tags, products or a category with Production Error Hunt: Axiom SRE Investigator (openclaw/clawhub, 9.5k stars), Code Design Rationale Investigator (cursor/plugins, 10k stars), Debug Mastery (xenitV1/claude-code-maestro, 229 stars) and Debugging and Error Recovery (addyosmani/agent-skills, 103k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Production Error Hunt?

different-ai (a GitHub organization) maintains it in different-ai/openwork, which has 23,943 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 8, 2026.

Source: different-ai/openwork on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.