diagnose
Investigate unexpected behavior and mysterious bugs. Use when the cause of a problem is unknown and the user needs to understand WHY something is happening — symptoms like: sudden unexplained changes in metrics or behavior, works locally but not in staging/production, inconsistent or intermittent failures, correct code producing wrong results, operations succeeding but having no effect, environment-specific failures, duplicate executions, stale data, or any \"why did this change?\" or \"why is this happening?\" situation. Covers infrastructure anomalies (cache hit rates dropping, latency spike
npx skills add majiayu000/claude-skill-registry --skill diagnose-avibebuilder-claude-prime --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
Think harder. ## Process Check conversation context and skip completed steps. ### 1. Understand the symptom - Read the bug report, errors, logs, and surrounding code carefully - Clarify reproduction steps, expected behavior, and environment when they are unclear - **Separate confirmed facts from working assumptions.** List them explicitly: - `Fact (confirmed):` the server returns 200 - `Assumption (unconfirmed):` the client receives the full HTML body Misidentifying an assumption as a fact is the most common source of wasted investigation. ### 2. Build hypotheses - Form 2-4 plausible root-cause hypotheses that are **mechanistically distinct** — different failure layers (e.g., server render vs. client hydration vs. network layer), not variations of the same idea - Rank them by likelihood - For each hypothesis, state both sides: - `Confirm if:` [what observation would prove this is the cause] - `Eliminate if:` [what observation would rule this out] A hypothesis you can't falsify in both directions is too vague to test. ### 3. Choose the lightest evidence method Start with the cheapest source of truth that can kill hypotheses: - existing logs, traces, stack traces, metrics, and error
- Process
- 1. Understand the symptom
- 2. Build hypotheses
- 3. Choose the lightest evidence method
- 4. Gather evidence and iterate
- 5. Report the diagnosis
- Constraints
- Bug
What does the diagnose skill do?
Investigate unexpected behavior and mysterious bugs. Use when the cause of a problem is unknown and the user needs to understand WHY something is happening — symptoms like: sudden unexplained changes in metrics or behavior, works locally but not in staging/production, inconsistent or intermittent failures, correct code producing wrong results, operations succeeding but having no effect, environment-specific failures, duplicate executions, stale data, or any \"why did this change?\" or \"why is this happening?\" situation. Covers infrastructure anomalies (cache hit rates dropping, latency spike
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill diagnose-avibebuilder-claude-prime --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.