diagnosing-superpower

diagnosing-superpower is a skill for Claude Code from baleen37/bstack. It costs 92 tokens per session (1,635 once invoked), scanned A, a copy of diagnosing-superpowers, MIT.

A workflow for investigating why a Superpower session went wrong, using saved conversation records as evidence. It reports what happened rather than deciding how the underlying system should be changed.

In plain words
What is it for?
Use it to investigate a failed skill invocation, repeated actions, poor results, slow work, or a possible bug report, with each finding linked to a file and line.
Why use it?
It replaces guesses about repeated work, missed steps, cost, or delays with findings tied to the session record. It also helps turn a vague complaint into a specific problem statement.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions subagents.

Part of the superpower plugin — 12 skills shipped together

Good fit Use it to investigate a failed skill invocation, repeated actions, poor results, slow work, or a possible bug report, with each finding linked to a file and line.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/baleen37/bstack/diagnosing-superpower
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.

Any agent
npx skills add baleen37/bstack --skill diagnosing-superpower
Clone the repo
git clone --depth 1 https://github.com/baleen37/bstack

Made for: Claude Code.

Or install superpower, the plugin that ships this one along with the rest of its 12 skills.

Wrote 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.

agentmods badge for diagnosing-superpower

README.md
[![agentmods](https://agentmods.dev/badge/skills/baleen37/bstack/diagnosing-superpower/github.svg)](https://agentmods.dev/skills/baleen37/bstack/diagnosing-superpower)
Your own site
<a href="https://agentmods.dev/skills/baleen37/bstack/diagnosing-superpower"><img src="https://agentmods.dev/badge/skills/baleen37/bstack/diagnosing-superpower/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.

agentmods 80×15 button for diagnosing-superpower

Your own site · 80×15
<a href="https://agentmods.dev/skills/baleen37/bstack/diagnosing-superpower"><img src="https://agentmods.dev/badge/skills/baleen37/bstack/diagnosing-superpower.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 92 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,635 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 94% copy Near-identical to another mod 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 5.1 $0.00092 $0.01635
Opus 5.5 $0.00037 $0.00654
Sonnet 5.5 $0.00018 $0.00327
Haiku 4.5 $0.00009 $0.00163

Measured 13d ago against content hash 58c4ff1ba8c3, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

diagnosing-superpower 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 13d 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.

Origin

This is a copy

94% identical to diagnosing-superpowers — 16 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/superpower/skills/diagnosing-superpower/SKILL.md · 121 lines

How it starts

The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Diagnosing Superpower

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 superpower. Whoever triages the bundle or the issue decides whether superpower 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 superpower 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 ~/.bstack/diagnosing-superpower/<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.

Read the full file on GitHub · 121 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. 13d ago First seen · 121 lines · 92 tokens per session scan A 58c4ff1ba8c3

Subscribe to this mod's changes

diagnosing-superpower is a skill published in the GitHub repository baleen37/bstack (4 stars, last pushed 13d ago), licensed MIT. It adds 92 tokens to every session and 1,635 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to diagnosing-superpowers, differing in 16 lines, and is treated as a copy.

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