Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
日本語の概要は準備中です。原文の説明を表示しています。
Scientific debugging for bugs, flakes, failures, and performance regressions. Use when something is broken, throwing, failing, slow, nondeterministic, or when the user says diagnose/debug this. Builds a trusted repro loop, tests falsifiable hypotheses, installs a regression oracle, and routes durable findings back into ln-* planning.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Debug by scientific method: trusted repro loop, falsifiable hypotheses, one-variable probes, regression oracle. Do not fix by inspection unless the cause is already proven.
Bug, failure, flake, or regression to diagnose: $ARGUMENTS
Orient first:
memory/SPEC.md if present; use its lexicon and live invariants.memory/PLAN.md if present; identify the containing frontier item if one exists.HANDOFF.md if present.Write a 2-4 bullet orientation note: symptom, suspected seam, current feedback loop, proof standard.
This is the skill. A fast deterministic pass/fail loop makes the rest mechanical. No loop, no diagnosis.
Try, in rough order:
Improve the loop before moving on: faster, sharper assertion, less flake. Pin time, randomness, network, filesystem, and concurrency. For nondeterministic bugs, raise reproduction rate with repetition/stress until it is debuggable.
If no loop can be built, stop. Report what you tried and ask for access, logs, traces, fixtures, timestamped recordings, or permission for temporary instrumentation.
Run the loop. Confirm it demonstrates the reported bug, not a nearby failure.
Capture:
Lack of reproduction is allowed only as an explicit diagnosis result.
Generate 3-5 hypotheses before testing any one of them. Each hypothesis must predict an observation:
If [cause] is true, then [probe/change] will make [specific observation] happen.
Prefer hypotheses that distinguish seams or invariants from memory/SPEC.md. Show the ranking to the user when they are present; proceed if they are AFK.
Every probe maps to one prediction. Prefer debugger/REPL inspection, then targeted boundary logs, then temporary assertions/counters.
Tag temporary instrumentation with a unique prefix like [DEBUG-a4f2]. Cleanup must be grep-able. Never "log everything and grep".
Performance branch: measure first. Establish a baseline timing/profiler/query-plan signal, then bisect or compare. Do not optimize before the measurement identifies the seam.
Before coding, choose the route:
ln-build — cause is proven and the change stays inside a settled seam.ln-scope or ln-spec — the fix changes a seam, invariant, requirement, assumption, or frontier shape.ln-spike or ln-design — diagnosis answered one question but the fix shape remains uncertain.ln-review / ln-refactor — no correct regression seam exists, or architecture contributed to the bug.Install the regression oracle before the fix when a correct seam exists. A correct seam reproduces the real bug pattern as it occurs at the call site. Shallow tests that cannot fail for the original bug are false confidence.
Before declaring done:
[DEBUG-...] instrumentation is removedAsk: what would have prevented this bug? Route missing invariants, unclear seams, weak oracles, and bad module shapes into the appropriate ln-* skill.
Reconcile only durable truth:
memory/SPEC.md §Assumptions.memory/SPEC.md or route to ln-oracles.memory/PLAN.md.Do not create CONTEXT.md, ADRs, or alternate planning docs. Canonical docs are memory/SPEC.md and memory/PLAN.md.
## Diagnosis: [symptom]
**Repro loop:** [command/script/test and reproduction rate]
**Confirmed cause:** [one sentence]
**Evidence:** [key observations]
**Fix route:** [direct fix | ln-scope | ln-build | ln-spike | ln-review | ln-refactor]
**Regression oracle:** [test/harness or why unavailable]
**Canonical updates:** [none | specific SPEC/PLAN changes needed]
After diagnosis, present these options to the user (use tool-ask-question):
| # | Label | Target | Why |
|---|---|---|---|
| 1 | Scope the fix | ln-scope | The fix needs a buildable card or durable seam update |
| 2 | Build the fix | ln-build | The fix is settled and ready for red-green-refactor |
| 3 | Spike deeper | ln-spike | A hard question remains after reproduction |
| 4 | Review structure | ln-review | No good seam/regression oracle exists or architecture contributed |
| 5 | Back to triage | ln-consult | Diagnosis changed priority or scope |
Recommended: 2 only when cause and seam are proven; otherwise 1.
Adapted from mattpocock/skills/engineering/diagnose.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
日本語の概要は準備中です。原文の説明を表示しています。
Search the live web via Perplexity Search API. Use when you need current documentation, release notes, vendor pages, news, domain-constrained web search, or date/recency filtering. Not for local codebase search or stable docs already in context.
日本語の概要は準備中です。原文の説明を表示しています。
Chrome DevTools CLI for browser automation via shell commands. Use when interacting with web pages from the command line — navigating, clicking, filling forms, inspecting console/network, taking screenshots, or extracting page content. Triggers on: browse a page, automate Chrome, inspect console, check network requests, take a screenshot, fill a form, click a button.
日本語の概要は準備中です。原文の説明を表示しています。
Uses the chrome-devtools-axi CLI for browser automation, accessibility-tree snapshots, console and network inspection, screenshots, Lighthouse audits, and performance traces. Use when interacting with Chrome from the shell, especially when the user mentions chrome-devtools-axi, AX snapshots, browser debugging, or DevTools automation from the command line.
日本語の概要は準備中です。原文の説明を表示しています。
Deep expertise in cmux — the terminal multiplexer with native browser views. Use when managing panes, reading terminal output, sending keystrokes, opening browser views, or manually testing web UIs and TUIs inside cmux. Triggers on: cmux, open a browser pane, split terminal, read screen, send keys, test this UI in cmux, preview in cmux.
日本語の概要は準備中です。原文の説明を表示しています。
Uses the gh-axi CLI for GitHub shell operations: issue, pull request, workflow run, release, repo, search, and API tasks. Prefer this over regular `gh` for GitHub reads and simple mutations when an agent needs compact, structured, suggestion-rich output. Triggers on: gh, GitHub CLI, github issue, github pr, pull request, workflow run, github release, gh api, repo inspection, list PRs, view issue, check workflow runs, inspect repo, GitHub shell operations.
日本語の概要は準備中です。原文の説明を表示しています。