「failure」の検索結果

Auto-selects and enforces the strongest valid Python typing lane for the detected Python version and dependencies — no user input required. Use when adding or tightening type annotations, eliminating Any usage in internal code, designing boundary validators or parsers, choosing between stdlib typing (TypedDict, Protocol, dataclasses), Pydantic models, or Hypothesis property tests, addressing ty or mypy failures, or applying version-specific features (TypeIs, ReadOnly, PEP 695 generics, PEP 649 deferred evaluation). Enforces boundary isolation — raw payloads validated immediately at ingress and returned as typed internal objects.

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Activates on any Python task involving *.py files, uv, ruff, ty, pytest, or pyproject.toml — loads the shared Python 3.11+ standards and routes the task to the specialist skill that applies them: TDD, CLI, web, data, async, typing, packaging, publishing, documentation sites, test design, test-failure analysis, or stdlib-only constrained environments.

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Scan Claude Code session transcripts to find the strongest user reactions to assistant instruction-following failures, reconstruct the triggering assistant output, and render a shareable terminal-style PNG artifact. Use when you want to surface and share a moment where the assistant completely missed what was asked — captures what they were doing, what Claude said, and how the user reacted. Triggers on: "rtfp", "read the fucking prompt", "find my worst AI moment", "make a rage screenshot from this session".

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Knowledge reference for Autonomous Refinement Loop research — pattern research into prerequisites for autonomous execution without synchronous human blocking gates. Defines failure categories, prerequisites, and conditions for replacing human judgment with machine-verifiable checks. Use when designing or evaluating autonomous agent loops, gate conditions, or HOOTL execution patterns.

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Use when asked to find a rage moment, analyze a direct transcript path, or analyze a session time range. RTFP finds the strongest instruction-following failure in Claude or Codex sessions and renders a rage receipt.

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Review changed user-interface or CLI presentation behavior for accessibility failures. Use for an independent accessibility perspective on a defined change set.

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Review a change for security defects such as secret exposure, injection, authentication/authorization failures, unsafe deserialization, and dependency risk. Use for an independent security perspective on a defined change set.

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Discover and run configured quality gates for requested or changed work, preserve diagnostics as evidence, route failures to the appropriate causal/domain capability, and verify corrections. Use for linting, formatting, type-checking, configured hook checks, or pre-completion quality verification.

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Use when investigating failing tests or deciding whether to change the test or product. Validate test expectations against authoritative intent, trace product and test boundaries, and require evidence for the correction rather than automatic code fixes or test dismissal.

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Write and evaluate effective Python tests using pytest. Use when writing tests, reviewing test code, debugging test failures, or improving test coverage. Covers test design, fixtures, parameterization, mocking, and async testing.

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Reviews Node.js runtime behavior in JavaScript or TypeScript, including server entrypoints, route handlers, middleware, streams, processes, dependencies, and environment configuration. Loads alongside language and CLI checks when applicable; investigates blocking I/O, backpressure, injection, lifecycle leaks, and misleading failure signals.

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Execute structured acceptance checks and record their observed results for later comparison. Use to capture a pre-change baseline or a post-change verification state without treating expected nonzero baseline results as execution failure.

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Reviews a whole deliverable (talk, course module, paper, chapter, or referee report) against its manifest without rewriting it. Runs a deterministic gate for build, citations, numbers, facts, and leaks and stops on failure, then runs a finder over each section and a strong-model pass over the whole work, and adjudicates into checks/<date>/findings.json and report.md with anchored findings, severities, and honest NOT CHECKED coverage within a dollar budget. Use when asked to lint or review the whole talk, module, or paper, for a pre-ship review, or for the night shift. Revision stays serial and author-led.

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Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

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Multi-step reasoning engine for complex analysis and systematic problem solving. Use when: (1) Complex debugging scenarios with multiple layers, (2) Architectural analysis and system design, (3) Problems requiring hypothesis testing and validation, (4) Multi-component failure investigation, (5) Performance bottleneck identification. Triggers: "--think", "--think-hard", "--ultrathink", "analyze step by step", "break down this problem", "systematic analysis". IMPORTANT: Do NOT use for simple single-step tasks.

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Track and report agent invocation metrics including usage counts, success/failure rates, and completion times. Use for understanding which agents are utilized, identifying underused agents, and optimizing agent delegation patterns.

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Handle failures and errors during workflow. Use when build breaks, tests fail unexpectedly, or agent gets stuck. Semi-automatic recovery with user confirmation for destructive actions.

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Senior engineer conducting thorough, constructive code reviews. Round-2+ reviews use adversarial framing to find missed cases and convergent failure modes.

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Audit AuthCrunch security boundaries, triage vulnerability reports and scanner findings, reproduce authentication or authorization failures, and prepare evidence-backed remediation. Covers trust, credentials, redirects, concurrency, diagnostic logging, and dependency exposure.

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Core agent-browser usage guide. Read this before running any agent-browser commands. Covers the snapshot-and-ref workflow, navigating pages, interacting with elements (click, fill, type, select), extracting text and data, taking screenshots, managing tabs, handling forms and auth, waiting for content, running multiple browser sessions in parallel, and troubleshooting common failures. Use when the user asks to interact with a website, fill a form, click something, extract data, take a screenshot, log into a site, test a web app, or automate any browser task.

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Use when reviewing, debugging, or hardening Shell/Bash scripts in this repo (.github/workflows/*.yml steps, website build scripts, or any *.sh file) or when asked to "review bash", "revisa el script", "shellcheck", or "revisa el pipeline shell". Reviews for robustness, error handling, quoting, portability, injection, and CI-friendliness, and ends with what a CI failure or a hostile input would catch.

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Portable Codebase Argus agent playbook for evidence-first multi-agent review of GitHub pull requests, CI failures, GitHub Actions logs, GitHub App webhook review, /argus PR comment commands, autofix branch planning, OpenAI/Claude/Gemini/Codex provider tribunals, downstream merge/rebase work, and long-lived fork sync against an upstream repository.

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Run a learning retrospective on the Kai harness. Mines gate-failure logs and 30-day performance results into lessons, triages candidate lessons (promote/keep/retire), and graduates repeated lessons into enforced gate checks with golden corpus cases. Use when "retro", "what have we learned", "triage lessons", "promote lessons", "why does this keep failing", "harness retrospective", or monthly / after any heavy content sprint.

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Testing patterns for PHPUnit tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ATmosphere features.

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。