「evidence」の検索結果

Read-only first workflow for diagnosing application incidents by collecting service, log, network, configuration, and functional evidence before proposing any 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。

GStack investigation method for bugs, incidents, failing tests, regressions, and unclear behavior where evidence and root cause should precede fixes.

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。

Produces a deep, honest peer-review of how someone uses Claude Code by statistically analyzing their local session data (~/.claude/usage-data/ and ~/.claude/projects/). Trigger whenever the user asks to review, analyze, audit, or critique their own Claude Code usage, workflow, habits, or skill level — including phrases like "analyze my cc usage", "review my cc sessions", "peer review my cc workflow", "deeper than /insights", or any ask for an honest audit of their AI workflow. Also covers portfolio/hiring-manager framings (e.g. "portfolio for Anthropic/OpenAI/xAI"), but ALWAYS ask the user in Step 0 which version to build (self / hr / both) before running — never silently produce an HR report, because that version goes to outsiders and needs explicit privacy setup. The HTML report is laid out ledger-first for SELF (opening band, output/team/leak/trend ledgers, then peer review, 9-dim scoring, try-this-week, case study, claim-indexed evidence). The HR variant is a recruiter version v1: identity card, earned badges (threshold-based, earned-only), allowlist-filtered output ledger, one case study, and a methodology & scope disclosure — no scores, no peer-review memo, no charts.

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。

Symptom → root-cause lookup table for nuxt-crouton's recurring failure modes — exact error strings mapped to their known cause, fix, and evidence issue. Use when you hit an error you don't recognize in this repo, before debugging from first principles. Trigger phrases and symptoms: "Cannot resolve entry module .nuxt/hub/db/schema.entry.ts", "Could not load '@fyit/crouton'", "No migrations present", "No schema files found", "$setup.t is not a function", "does not provide an export named 'Map'", "no such table: translations_ui", "collection pages 500 in production", "the build was green but the app is broken", "is this a known issue?".

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。

The case-law chronicle of this repo's major failures — symptom, root cause, evidence, status, and the rule each battle minted — so nobody re-fights a settled battle or re-proposes a rejected fix. Use when a bug/incident looks familiar ("didn't this happen before?"), when you're about to propose an approach that may have been tried and rejected (e.g. shipping a migration from a package), when someone asks "why does rule X exist" / "why is done-by-lgtm a thing" / "what was incident 988", or when a bug-archaeology run hits the shallow-clone wall and needs the pre-June-2026 history. Trigger phrases: "has this broken before", "why can't packages ship migrations", "why did graduation fail", "why is the green-build lesson a rule", "what did we learn from incident NN". (For a live "build is green but the app is broken" symptom, start at crouton-diagnostics-index. NB keep this description free of any space-then-hash sequence — an unquoted YAML scalar treats space-hash as a comment start and silently truncates.)

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。

At the close of an epic (or a difficult issue), post a postmortem roundup comment — what went well, what was hard (backed by evidence), and 1–3 concrete proposals to improve the skills/flows — then offer to turn accepted proposals into their own `workflow`-labeled tasks, and end with a `🔭 Next` handoff (a paste-ready next-session prompt + the next epic to start). Use at epic close, after the "verify the whole thing" rollup, or when asked to "do a retro", "postmortem this epic", "what did we learn", "how do we improve the workflow".

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。

A pessimistic go/no-go the moment you pick up a GitHub issue — read it skeptically and hunt for reasons NOT to do it (already done? obsolete? duplicate? premise wrong? cheaper way? net-negative?), returning proceed / reshape / drop with one-line evidence. The pickup-time half of the dedup gate (the create-time half is /issue-dedup). Use as step 1 of the Task Execution Workflow, or run /issue-sanity-check

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。

Record a WebM demo video of a UI flow with shot-scraper video — a YAML storyboard drives the browser (click, type, scroll, wait) with an animated cursor overlay, so a reviewer can watch the feature instead of driving it. Use to attach motion evidence to a UI sign-off (#307), to turn an issue's "How to test" steps into a watchable clip, or when asked to "record a demo", "make a video of this flow", "show me it working".

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。

How to actually run every kind of test in nuxt-crouton (unit/e2e/typecheck/lint, verified commands) plus the HONEST coverage picture — which packages have real tests vs zero, the dormant skipped/todo cases behind three mocking walls, and what CI truly gates vs what CLAUDE.md claims. Use when asked "how do I run the tests", "is X covered by tests", "what does CI actually check", "why is this suite skipped", "where do I add a test", or before trusting a green build as evidence that something works.

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。

Draft and revise evidence-grounded academic manuscripts with adaptable author preferences. Use for section writing, implementing structural edits, claim calibration, citation-integrated prose, prose cleanup, standalone review excerpts, and LaTeX template migration. Use paper-review for critique or author responses, and paper-figures-tables for final visual artifacts.

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 auditing a repository for evidence-backed gaps between code, SPECs, architecture, and documentation — before a release, after a review, or when the user asks what is missing or divergent. Confirmed gaps become Draft SPECs via write-specs, a tracked GitHub Epic via create-issues, and orchestrated execution via orchestrator, with an explicit approval gate before any external action.

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 planning the migration of a legacy system or monolith — analyzes the source codebase (current repo, or a repo URL cloned to a temp dir) and produces an evidence-based Strangler Fig migration plan with per-domain SPECs. Default target is .NET (Blazor WebAssembly, .NET MAUI, ASP.NET Core); other stacks allowed by user decision. Do NOT use to implement code or when approved SPECs already cover the migration.

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 auditing UI code for interface-guideline compliance (accessibility, forms, animation, images, performance, UX copy) and/or validating a deployed page against Lighthouse 95+ targets. Produces evidence-based findings (file:line + Lighthouse JSON) and turns confirmed pendencies into Draft SPECs via write-specs. Do NOT use to design/build UI from scratch (use design) or to fix findings inline — fixes go through the SPEC pipeline.

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。

Draws an interactive HTML Architecture Viewer for any code flow the user names. Walks through seven research-driven steps (flow, name, repo research, lens colors, evidence flags, lens+mechanism per stop, build) and verifies links, claims, and generated artifacts before delivery.

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。

Research and stress-test open-source project names, from collision checks to launch-ready decisions. Use when the user asks to name or rename a project, compare candidate names, screen GitHub or package namespace risk, verify language or mythology claims, or improve SEO/GEO clarity. Perform live web and registry research, separate brand from category descriptor, classify collisions, and return one evidence-backed recommendation.

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 work is ambiguous or has multiple viable paths; compares options, assumptions, evidence, tradeoffs, and the best next action.

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 work needs deeper thinking, less generic output, repo evidence, tradeoffs, monitoring signals, or stronger quality discipline.

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 before completion, PR, deploy, handoff, or when verifying code changes. Runs advisory or blocking checks and reports evidence.

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。

Conduct reproducible web searches and decision-oriented research across official sites, search engines, news, papers, forums, social platforms, and public datasets. Use when Codex must investigate a person, organization, product, market, technical resource, reputation, career choice, or other current topic; compare candidates; verify claims; collect dated citations; distinguish facts from inference and anecdote; or write an evidence-backed research report.

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。

Reconstruct an evidenced indoor space from local Realsee scan exports, point clouds, CAD, and panoramas as a separately editable native Blender scene. Use for scan-to-Blender space modeling, source-based geometry/material/light refinement, and requested walkthrough or physics exports. Argus panorama-to-depth inference is a separate capability.

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。

Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.

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。

Read the Convex deployment's 72h insights (read limits, OCC contention), root-cause each event in code, report evidence-backed perf/cost findings with fixes.

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。

Read the Convex deployment's 72h insights (read limits, OCC contention), root-cause each event in code, report evidence-backed perf/cost findings with fixes.

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。

Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.

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。