「root cause」の検索結果

Root-causes one specific mistake the agent just made, such as not committing despite instructions to, by checking it against the loaded AGENTS.md, CLAUDE.md, skills, and Beads memories, delegating the investigation to a separate agent where the harness supports one; proposes concrete context improvements, and lets the user choose which to apply and how to remediate. Use when the user invokes `/learn` or `$learn`, with or without a description of the mistake, including `/learn /qs`-style shorthand naming the corrective command. For a broad end-of-session documentation sweep, use `documentation-updates` (`/reflect`) instead.

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Capture durable project or workflow knowledge discovered during work. Use when a mistake, hidden constraint, repeated question, or changed behavior reveals a documentation gap. To root-cause one specific mistake the agent just made and let the user pick fixes, use `learn` (`/learn`) instead.

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。

Diagnoses and fixes bugs, type/lint errors, CI failures, and runtime errors, root-cause first. NOT for investigation without a fix (mk:investigate) or build-only compile errors (mk:build-fix).

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Use when autonomously improving a measurable scalar metric through bounded, git-tracked iterations: modify one scoped change, verify, keep or revert. Triggers on /mk:loop, 'optimize coverage/bundle size/lint count', 'iterate until the metric improves'. NOT for subjective cleanup (see mk:cook), known-root-cause bugs (see mk:fix), behavioral grading (see mk:evaluate), or shipping (see mk:ship).

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。

Use when a problem requires structured step-by-step reasoning before acting. Prevents jumping to conclusions or guessing root causes without evidence. Triggers on complex debugging, multi-step analysis, hypothesis verification, or when mk:fix invokes diagnosis phase. NOT for being stuck on approach (too many implementations, forced assumptions, innovation block) — use mk:problem-solving instead.

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Use when a decision needs deep multi-source technical research with cited evidence — technology evaluation, ecosystem comparison, standards/spec fact-finding, "how do others solve X". Triggers on "research X", "deep dive on X", "evaluate X vs Y", "find best practices for X". NOT for library/API doc lookup (see mk:docs-finder); NOT for one-shot URL fetch (see mk:web-to-markdown); NOT for internal codebase discovery (see mk:scout); NOT for project-only Q&A (see mk:ask-me); NOT for comparing solution designs (see mk:brainstorming); NOT for root-cause debugging (see mk:investigate); NOT for wiki ingestion of sources (see mk:wiki-research).

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。

Use when stuck on approach (not debugging). Strategic unsticking via 7 non-default techniques: simplification cascades, collision-zone thinking, meta-pattern recognition, inversion, scale game, first principles, via negativa. Triggers on complexity spiraling, innovation block, recurring patterns across domains, forced-assumption solutions, scale uncertainty, told-it's-impossible, or bloated systems needing subtraction. For evidence-based root-cause debugging, use mk:sequential-thinking instead.

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。

Diagnoses and fixes bugs, type errors, lint failures, CI/CD issues, and runtime errors via root-cause-first investigation. Use for defect remediation. NOT for investigation without a fix (see mk:investigate); NOT for build-only compilation errors (see mk:build-fix).

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。

Use when answering factual or explanatory questions about the current project — codebase, architecture, conventions, workflows, constraints — with minimal cited evidence. Triggers on "how does X work here", "what does X mean", "why is X structured this way", "is this claim true in the repo", "explain X with sources". NOT for brainstorming or comparing approaches (mk:brainstorming), trade-off decisions (mk:party), debugging/root cause (mk:investigate), code review (mk:review), plans (mk:plan-creator), security audits (mk:cso), visual explanations/diagrams (mk:preview --explain), test-coverage gaps (mk:nyquist), library docs (mk:docs-finder), or workflow navigation (mk:help).

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。

Use when encountering any bug, test failure, or unexpected behavior. Enforces a strict reproduce-first, root-cause-first, failing-test-first debugging workflow before fixing.

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Deterministically score comparable imported review-run lanes with root-cause metrics and uncertainty. Use only when the user explicitly asks to benchmark normalized local review runs or use the bundled synthetic fixture.

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。

Call this skill when faced with "wicked problems", complex challenges, or when a user asks for strategic innovation, root-cause analysis, or long-term problem solving. Do not use for simple, linear tasks. This skill forces the agent to bypass superficial symptoms, map the entire ecosystem, and anticipate second-order consequences before proposing an intervention.

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Naturalistic causal reasoning for failures and disputed attribution. Use when postmortems or root-cause debates need reframing. NOT for causal inference, fault trees, or fully observed failures.

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Systematically interpret a Medtronic CareLink or MiniMed 780G Daily Review download in a structured 6-step clinical workflow — covering Time in Range, insulin delivery, day/night patterns, hypo and hyperglycemia root causes, and a prioritised action plan. Trigger when a clinician uploads or shares a CareLink report, MiniMed download, 780G Daily Review, pump download, or asks to review a patient's CGM or insulin pump data.

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Draft a Root Cause Analysis for an incident, outage, or repeated test failure. Unlike intake/spec/brd, RCA is not a workflow phase — it's a standalone postmortem artifact that often precedes a bugfix intake. Output lives at `docs/rca/<slug>.md`.

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。

Trace bugs backward to their origin, not just symptoms

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。

Debug like Fable 5 — systematic root cause analysis with natural reasoning flow. Use this skill when you encounter an error, unexpected behavior, failing tests, or anything that does not work as intended.

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。

4-phase root cause debugging: understand bugs before fixing.

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。

Systematically find root causes and fix bugs. Use when debugging errors, investigating test failures, reproducing bugs from issue trackers (GitHub, Linear, Jira), or when stuck on a problem after failed fix attempts. Also use when the user says 'debug this', 'why is this failing', 'fix this bug', 'trace this error', or pastes stack traces, error messages, or issue references.

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。

Perform a deep architectural analysis or security review requiring extended reasoning. Use for complex architecture decisions, security audits, or when standard analysis is not finding the root cause.

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。

Diagnoses failing GitHub Actions runs by reading logs, identifying the root cause, and suggesting fixes. Use this skill whenever a user shares a GHA run URL, pastes runner log output, mentions a failing workflow, asks why a CI job is broken, or says anything like "my GHA is failing", "workflow failed", "can you check my run", or "CI is broken". Also trigger when raw log text is detected in the conversation that appears to come from a GitHub Actions runner. Do NOT use for general GHA workflow authoring questions, YAML formatting help, or passing runs with no failure context.

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Form a committee of two high-reasoning agents to step back, do root cause analysis, and produce a plan. Use when stuck, looping, tunnel-visioning, or facing a hard planning problem.

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Isolate the root cause of ML performance drops, inconsistent evaluations, prediction errors, and training-serving mismatches across data, labels, splits, pipelines, models, metrics, and runtime behavior. Use when investigating a reproducible failure or regression, not routine model selection or general performance validation.

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Measure, root-cause, fix, verify and record performance contention on a developer machine: cloud-sync daemons (iCloud Drive, OneDrive, Dropbox, Google Drive), file indexers, AI-tool MCP server fleets, and automation browsers left behind by tests and browser skills. Trigger when the machine is slow, apps freeze, browser or MCP tool calls time out, load exceeds the core count, or before and after any UI/UX/performance test run. Includes the L0–L4 optimisation scale and the test-hygiene contract.

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。