「detect」の検索結果

Benchmark external agent frameworks, auto-detect source type, scan for prompt injection, and convert findings into a concrete TDD upgrade backlog for agent-studio evolution.

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。

Orchestrates SDD project initialization — version detection, environment verification, scaffolding, and git setup.

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。

Writes and maintains user-facing documentation for the SDD plugin. Proactively detects when docs are out of sync with plugin capabilities.

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。

Displays installed and project plugin versions with mismatch detection.

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。

Detect and exploit subdomain takeover via dangling DNS records pointing to deprovisioned cloud services (S3, GitHub Pages, Heroku, Azure, Shopify, AWS CloudFront, etc.). Use after subdomain enumeration to identify takeover candidates.

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。

Rewrite text so it reads like a real person wrote it, not an AI. Auto-detects Russian vs English and applies the matching rule set. Use when the user asks to humanize text, remove the "AI smell", de-AI, or make AI output sound natural - especially for Russian. Russian requests count too - очеловечь, перепиши как человек, оживи текст, убери запах ИИ, сделай живее, звучит как робот, убери канцелярит. Also use when asked whether a text was written by AI - нейросеть писала?, похоже на ChatGPT?, видно ли, что это ИИ, человек или бот писал, did AI write this? - then check and report findings without rewriting. While installed, also keep your own Russian and English writing free of the quick-list stock phrases, silently; never edit the user's text unless asked.

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。

Set up a construction project — inventories files, classifies drawings/specs/schedules/registers, detects AgentCM mode, appends construction context to CLAUDE.md. Triggers: 'set up project', 'construction setup', 'classify documents'.

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。

Construction document review with PE judgment — RFI research, submittal analysis, coordination checking, scope gap detection. Use when reviewing drawings, specs, submittals, or RFIs. Triggers: 'review', 'coordination', 'what's missing'.

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。

Bootstrap a task into a synced feature branch — one shot, zero confirmations. Detects the source from the args: GitHub issue ('#100', 'issue 100', 'gh issue 100', or bare '100'), Jira key ('PROJ-42'), or a local spec file path; ad-hoc conversation otherwise. Fetches the task, derives {type}/{number}/{slug}, syncs the default branch, creates and pushes the branch, and writes specs/context/<id>.md. Use only when the user explicitly asks to start a task or create a work branch — never trigger automatically.

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。

Detect, validate, and generate Schema.org structured data. JSON-LD format preferred. Use when user says "schema", "structured data", "rich results", "JSON-LD", or "markup".

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。

Hreflang and international SEO audit, validation, and generation. Detects common mistakes, validates language/region codes, and generates correct hreflang implementations. Use when user says "hreflang", "i18n SEO", "international SEO", "multi-language", "multi-region", or "language tags".

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。

Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and industry-specific recommendations. Detects business type (brick-and-mortar, SAB, hybrid) and industry vertical (restaurant, healthcare, legal, home services, real estate, automotive). Use when user says "local SEO", "Google Business Profile", "GBP", "map pack", "local pack", "citations", "NAP consistency", "local rankings", "service area", "multi-location", or "local search".

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。

Full website SEO audit with parallel subagent delegation. Crawls up to 500 pages, detects business type, delegates to 7 specialists, generates health score. Use when user says "audit", "full SEO check", "analyze my site", or "website health 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。

Rebuild the knowledge base shelf-index with hash-based change detection. Incremental by default — only re-extracts files whose content has changed since the last index. Use after ingesting new sources, after editing library files, or whenever the librarian agent reports a stale index.

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。

Run all 5 decomposition validators (req-has-module, code-annotation-maps-to-module, visibility-rule-enforcement, anaemic-context-detection, granularity-match) on the project, reporting violations.

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。

Check whether the knowledge base shelf-index is stale relative to the library files. Reports drifted entries without rebuilding. Designed to be invoked from environment validation or pre-push hooks as an opt-in check. Default mode is warning; strict mode fails with non-zero exit when any drift is detected.

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。

Send, read, listen, respond, and manage SMS conversations via Telnyx and Twilio. Supports 8 phone numbers across both providers with auto-detection, conversation threading, MMS, real-time inbound listening, background watcher, batch reply processor, and soul-aware auto-reply. 10 Python scripts for SMS 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。

Evaluate design from a UX perspective with Nielsen's heuristics scoring, anti-pattern detection, persona-based testing, and actionable feedback. Report-only. Triggers on critique, UX review, design feedback, how does this look, evaluate the design, component review.

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, iterative, multi-source research that explores a topic from multiple perspectives, detects contradictions, and produces a comprehensive vault note with fact-level citations and a confidence map. Use this skill whenever the user says /deep-research, "deep research X", "research X thoroughly", "investigate X deeply", "I need to really understand X", or wants research that goes beyond a quick web search. Also use when the user wants to understand a complex, contested, or multi-faceted topic, compare competing approaches with evidence, or build a comprehensive mental model they can trust for decisions. This is heavier than /research — it searches web, academic papers, Reddit, and the vault, then loops through exploration and critique rounds until the evidence base is solid. When in doubt between /research and /deep-research, prefer this one if the topic is complex, contested, or the user wants depth over speed.

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。

Extract transcript and key slides from a local video file, then create a vault-formatted lecture note. Use this skill whenever a user provides a local video file (.mp4, .mov, .mkv, .avi, .webm) and wants notes from it. Triggers on "lecture", "take notes", "I have a recording of", "class video", "transcribe this presentation", "process this video for notes", or /lecture. Works with any language — auto-detects transcript language.

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。

Audits and scores Claude Projects using a six-dimension Scorecard with anchored 1-5 rubrics and detects seven structural anti-patterns. When global layer info is provided, adds cross-layer alignment findings. Use when user says "audit my project," "review my custom instructions," "score my project," "evaluate my Claude project," "improve my system prompt," "what's wrong with my project," "why is my project underperforming." Also trigger on symptom-phrased: "my project doesn't work right," "Claude is inconsistent in my project," "my Project used to work and now doesn't." Also use when the user pastes Custom Instructions asking why output is poor or generic. Do NOT use when the user's primary request is a global-layer audit (use rootnode-global-audit if available), single-prompt evaluation (use rootnode-prompt-validation if available), or Memory-only optimization (use rootnode-memory-optimization if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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。

Audits and optimizes the five global Claude layers (User Preferences, Styles, Global Memory, Skills, MCP Connectors) using the Global Layer Scorecard (six dimensions, anchored 1-5 rubrics). Detects eight cross-layer failure modes and produces evolutionary recommendations (Promotion, Demotion, Codification, Skill Extraction). Use when user says "audit my global setup," "optimize my preferences," "review my Claude configuration," "check my cross-project setup," "are my preferences working," "clean up my global memory," or "what should be in my preferences vs my project." Also use when a user has 3+ Projects and wants to improve their shared foundation. Do NOT use for single-Project audits, Project Memory optimization, or full-stack audits (use rootnode-project-audit, rootnode-memory-optimization, or rootnode-full-stack-audit respectively, if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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。

Independent re-derivation gate for proposed changes during autonomous execution. Evaluates a change (code diff, config edit, engine evolution, schema change) against the work's authority matrix and a 4-check protocol: invariant compliance, scope authorization, detection narrowness, and regression risk. Returns structured JSON with pass/fail per check, an overall verdict (APPROVE / REQUEST_CHANGES / REJECT), and blockers. Profile-driven thresholds (strict for unattended runs, lenient for desk supervision). Use when an autonomous agent proposes an engine change, when reviewing a Claude Code-authored modification before merge, or when an unattended profile requires independent re-derivation. Trigger on: "review/approve this proposed change," "critic-gate this," "is this change safe," "is this safe to merge," "should I let this land," "run the critic." Do NOT use for handoff-readiness checks (use rootnode-handoff-trigger-check), general code review, or design-time correctness. Authority matrix required.

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。

Medicinal chemistry filters for compound triage. Apply drug-likeness rules (Lipinski rule of five, Veber, Oprea, CNS, lead-like, rule of three), structural alert catalogs (PAINS a/b/c, NIBR screening-deck severity, Brenk, BMS, Glaxo, Dundee, ChEMBL common alerts), ZINC-15 percentile complexity metrics (Bertz, SAscore, QED, Whitlock, Barone), chemical-group detection, Lilly demerits, and the medchem query language (MATCHRULE, HASALERT, HASPROP, HASGROUP) for filtering a library at scale. Also trigger on medchem, `import medchem as mc`, RuleFilters, NIBRFilters, CommonAlertsFilters, NamedCatalogs, QueryFilter, PAINS filtering, or structural alerts.

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。