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dx-diagnose

Feedback-loop-first diagnosis for bugs and performance regressions.

Skill by dikamilo

IndexedMIT★ 8
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/dikamilo-dx-diagnose

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Feedback-loop-first diagnosis for bugs and performance regressions. Use when something misbehaves (errors, crashes, hangs, wrong output), got slower or flaky, or regressed — or when the user asks to debug or find the root cause of a defect or perf problem.

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Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/dx-diagnose

What's inside

Skill name
dx-diagnose
Description
Feedback-loop-first diagnosis for bugs and performance regressions. Use when something misbehaves (errors, crashes, hangs, wrong output), got slower or flaky, or regressed — or when the user asks to debug or find the root cause of a defect or perf problem.
License
MIT
Instructions
51 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# dx-diagnose

Find the cause of a bug or perf regression, then either fix it inline or **promote** it into a change. Feedback-loop-first: **no red-capable loop, no hypothesising.** Read `foundation/glossary.md` if present (one-line habit — name the symptom in the project's terms).

Ad-hoc by default: this runs on a raw symptom with no container. If invoked **mid-task** (e.g. during `/dx-implement`), finish diagnosing this bug, then suggest the next step — don't silently resume the interrupted skill.

## Phase 1 — Build a tight, red-capable loop *(this is the skill)*

Name **one command** — a failing test, curl, CLI diff, headless-browser script, trace replay, throwaway harness, fuzz/property loop, `git bisect run`, or differential run — that you have **already run once** (paste invocation + output) and that:

- **goes red on THIS bug** — drives the real code path and asserts the user's exact symptom (not "runs without erroring");
- is **deterministic** (flaky bugs: raise the reproduction rate until debuggable) and **fast** (seconds).

Spend your effort here — once a tight loop exists, most of the fix follows. If you genuinely cannot build one, stop and say so — list what you tried, ask for an environment/artifact/instrumentation. **Done when** that command exists and goes red. Catching yourself theorising before it exists is the exact failure this prevents.

## Phase 2 — Reproduce + minimise

Run the loop red. Confirm it is the **user's** symptom, not a nearby one. Then shrink to the smallest scenario that still goes red — cut inputs/callers/config **one at a time**, re-running each cut. **Done when** every remaining element is load-bearing.

## Phase 3 — Hypothesise (3–5, ranked, falsifiable)

Generate 3–5 hypotheses **before testing any** — single-hypothesis anchors on the first plausible idea. Each states its prediction: "if X is the cause, changing Y flips the verdict." No prediction → it's a vibe; sharpen or drop it. **Show the ranked list to the user before instrumenting** (they may re-rank instantly); proceed on your ranking if they're AFK.

## Phase 4 — Instrument (one variable at a time)

Each probe maps to one Phase-3 prediction. Prefer a debugger/REPL over logs; **tag every debug log** with a unique prefix (`[DEBUG-a4f2]`) so cleanup is one grep. For perf: measure a baseline first (profiler / timing / query plan), then bisect — never "log everything".

## Phase 5 — Fix + regression test

Write the regression test **first if a correct seam exists** — one exercising the real bug pattern at its call site. If the only seam is too shallow to catch it, **that absence is itself the finding** — note it. Fix, watch red→green, then re-run the Phase 1 loop against the original un-minimised scenario.

## Phase 6 — Cleanup + outcome

Original repro gone, regression test green (or missing-seam documented), all `[DEBUG-…]` removed, throwaway harnesses deleted. State the winning hypothesis. Then decide:

- **Trivial → ad-hoc, no container.** Fix stays inline, regression test stays. No artifacts. Never auto-rollback.
- **Non-trivial → PROMOTE.** Write `diagnosis.md` (minimised repro + ranked hypotheses + regression test) and run `/dx-new` stamped `type: defect` (which activates the TDD gate in `/dx-plan`), carrying that file as the change's seed. For the change's schema, invoke `dx-references` with topic `change-md`. `/dx-plan` reads `diagnosis.md` the way it reads research.

## Done when

Print the outcome and the next command, then **stop**:

```
Trivial:  Fixed inline: <one-line cause>. Regression test: <path>.
Promoted: Diagnosis written: context/changes/<id>/diagnosis.md
          Next: /dx-plan <id>   (defect → TDD gate)
```

Never chain into the next skill; never roll back without the user.

From dikamilo/dx-workflow, MIT.

More from dikamilo/dx-workflow

Signals

Stars
8
Forks
4
Open issues
0
Last commit (this folder)
Sep 24, 2026 (1 month ago)
Last release
Oct 7, 2026 (24 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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dx-diagnose skill. Agent Mart. https://agentmart.dev/skills/dikamilo-dx-diagnose (last updated 2026-10-24)