SKILL·D0FD9D

diagnosing-superpowers

obra
Updated 17 days ago
3 views
297,189
26,531
297,189
View on GitHub
Metaaidesign

About

This skill helps diagnose issues in superpowers sessions by analyzing transcripts and generating bug reports with specific evidence citations. It's triggered when sessions have problems like repeated work, poor results, or unexpected costs. The skill systematically examines session data while requiring every finding to reference specific transcript lines for accuracy.

Quick Install

Claude Code

Recommended
Primary
npx skills add obra/superpowers -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/obra/superpowers
Git CloneAlternative
git clone https://github.com/obra/superpowers.git ~/.claude/skills/diagnosing-superpowers

Copy and paste this command in Claude Code to install this skill

Documentation

Diagnosing Superpowers

Overview

Pin down with your human partner what went wrong in a session, read the transcripts on disk, and report what happened with evidence. You report; you do not diagnose superpowers. Whoever triages the bundle or the issue decides whether superpowers changes.

Core principle: Every finding cites path:line. No citation, no finding. Every number comes from the transcript or from a command you ran, never from memory.

Workflow

Create a todo per step. Steps 5–7 run only on their stated condition.

  1. Problem intake. Ask one question at a time until you can write a statement naming the session(s), the turn range if known, what your partner expected, what happened, and the observable they care about (wall-clock, tokens, repeated actions, one specific action). "It took too long" is a complaint, not a problem statement. Note whether the goal is a superpowers bug report.
  2. Locate. Resolve each session to verified absolute filesystem paths using references/session-discovery.md. Confirm a past session by quoting its first prompt and timestamp, and list every candidate you rejected with the reason, or "none". Enumerate subagent transcripts. Create ~/.superpowers/diagnosing-superpowers/<session-id>/, tell your partner the path, and fill templates/case.md there, following its provenance rules for environment and skill observations.
  3. Triage. Read the region around the reported problem yourself. Then dispatch one analyst subagent per dimension in parallel, each given the case file path, prompts/analyst-common.md, and one dimension file from prompts/: skill-timeline.md, plan-adherence.md, repeated-work.md, stumbles.md, quality-evidence.md, request-conflicts.md, cost-and-time.md. Split a dimension by turn range when the transcript is long. Discard any returned finding without path:line.
  4. Report. Fill every section of templates/report.md in order, write it to the workspace, show it, and give the path. Check what cited content actually proves and preserve the supporting case; a symlink alias is not a redundant copy.
  5. GitHub issues — when report §7 says possible or likely, or your partner asks. Search open and closed issues for the symptoms per references/github-issues.md. Show matches and suggest adding the report to the closest. If none match, fill templates/issue.md, write it to the workspace, show the exact text, and create the issue only after approval. gh cannot attach files; if a bundle exists, give your partner its path to attach in the browser.
  6. Export — only when your partner asks for a bundle; never build one unprompted. If the intake goal was a bug report, say once that a scrubbed bundle is available on request, then wait. Ask the redaction level, stating what each includes: skeleton (no tool-result bodies), evidence (bodies only for cited events), full. Build the bundle per templates/bundle-README.md, dispatch prompts/scrub.md, then prompts/scrub-audit.md, repeating both until the audit returns CLEAN. Complete the bundle template's evidence check and reconciliation before showing the final scrub log, file list, and privacy and evidence outcomes. Archive (zip -r or tar -czf) only after approval. With the archive path, state what it contains, point at the scrub log for replacements, and say scrubbing can miss things: they must review every file before sharing.
  7. Similar sessions — when asked. Turn confirmed findings into a signature, list candidates by mtime and size, find marker line numbers, dispatch prompts/similar-session.md per candidate in parallel, and append report §9.

Quick reference

All seven analysts always run. This table says which region to read yourself in step 3 and which findings to lead with in the verdict.

ComplaintRead first, lead with
"It took too long"cost-and-time, stumbles
"Why did it do this extra work?"repeated-work, plan-adherence
"Why is it so expensive?"cost-and-time
"What the hell is it doing?" (still running)skill-timeline; note in-progress in coverage
"It ignored the plan"plan-adherence, compaction lines first
"Skill X never fired"skill-timeline

Hard rules

  • Context safety. One transcript line can be a megabyte. Follow references/context-safety.md on every session file, every time.
  • Read-only. Never modify, move, or delete a session file.
  • Exact paths to subagents. A subagent's "current session" is its own. Pass absolute paths and ids.
  • Human prompts only. Hook output, system reminders, and tool results are not your partner's words. In a subagent transcript, "user" is the parent agent.
  • No superpowers diagnosis. Report §7 states involvement and stops. Never name a defect in a skill or propose a change. Your partner pressing for a fix does not waive this; point at the issue step and mention that a bundle is available on request. No advice to your partner either.
  • Approval gates. No archive before your partner has seen the scrub log and file list. No issue or comment before they approve the exact text.
  • Intake before analysis. Nothing in steps 2–7 starts until your partner has answered. If they are away, write the questions and stop. A statement you reconstructed for them is not an answer. An already-scoped request — one specific event, what is running now, or the analysis to run — is itself the statement: answer it, then ask. A whole-session "why" is a complaint.

Red Flags

ThoughtReality
"The problem is obvious, skip intake"The problem statement scopes everything. Ask.
"They're away, so I'll reconstruct the statement"You cannot reconstruct what they wanted. Write the questions and stop.
"I'll sweep everything now and ask at the end"An unscoped sweep spends their budget on the wrong question. Ask first.
"They want a bug report, so I'll build the bundle now"The bundle is their session data, packaged. Build it only when they ask for it.
"Small, targeted edit, no restructuring needed"Not your call, however small. Report the evidence; the triager decides.
"The price per token is well known"Numbers you did not compute from the transcript are invented. Cite or drop.

GitHub Repository

obra/superpowers
Path: skills/diagnosing-superpowers
0
aibrainstormingcodingobrasdlcskills
FAQ

Frequently asked questions

What is the diagnosing-superpowers skill?

diagnosing-superpowers is a Claude Skill by obra. Skills package instructions and resources that Claude loads on demand, so Claude can perform diagnosing-superpowers-related tasks without extra prompting.

How do I install diagnosing-superpowers?

Use the install commands on this page: add diagnosing-superpowers to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.

What category does diagnosing-superpowers belong to?

diagnosing-superpowers is in the Meta category.

Is diagnosing-superpowers free to use?

Yes. diagnosing-superpowers is listed on AIMCP and free to install.

Related Skills

content-collections
Meta

This skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.

View skill
polymarket
Meta

This skill enables developers to build applications with the Polymarket prediction markets platform, including API integration for trading and market data. It also provides real-time data streaming via WebSocket to monitor live trades and market activity. Use it for implementing trading strategies or creating tools that process live market updates.

View skill
creating-opencode-plugins
Meta

This skill helps developers create OpenCode plugins that hook into 25+ event types like commands, files, and LSP operations. It provides the plugin structure, event API specifications, and implementation patterns for JavaScript/TypeScript modules. Use it when you need to intercept, monitor, or extend the OpenCode AI assistant's lifecycle with custom event-driven logic.

View skill
sglang
Meta

SGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.

View skill