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概要と使いどころ
Convert scattered progress notes, RAID changes, and milestone movement into a clean weekly or biweekly status update. Use when the work is routine status packaging or steering prep. Do not use for project governance design, root cause analysis, or deep portfolio risk assessment.
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Application-level business logic security testing for any domain. Takes an understanding-first approach: map the intended workflows before probing them. Covers: value/quantity logic abuse (negative, zero, overflow, rounding on any numeric field), workflow and state machine bypass (skipping required steps, forcing illegal state transitions, reusing one-time tokens), trust boundary violations (BOLA horizontal/vertical, BFLA, cross-tenant access, negative ownership attacks), idempotency and replay attacks (duplicate submissions, double-spend, same-reference reuse), multi-step flow integrity (checkout, registration, approval, verification), quota and rate limit bypass, time/date manipulation, and authorization code / reference number predictability. Domain-agnostic — applies to SaaS, e-commerce, banking, gaming, social platforms, APIs, or any multi-user application with stateful workflows. Chains from /pentester; chains into /param-fuzz when boundary violations or mass assignment are confirmed.
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。
Design or revise Interpreter UI for non-developers with an ultra-minimal, utilitarian style inspired by the OpenAI website and ChatGPT, not the developer platform. Use when simplifying settings, onboarding, chat, forms, empty states, or helper copy; when removing extra containers, labels, or visual noise; when replacing technical wording with plain language; when clarifying hierarchy and making the main user action obvious; when making every visible label and status understandable to an average HR admin or other non-technical user; when hiding implementation details such as logs, IDs, endpoints, paths, or protocol names; or when a screen must respect the app's existing CSS variables and light/dark theme behavior.
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。
Drive a native desktop app through Interpreter's builtin-cua-driver. Use get_app_state, click/type/scroll/drag, and verify by calling get_app_state again when the user asks to operate a real desktop app, browser chrome, native dialog, menu, secure prompt, file chooser, or hidden/background window.
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。
Pinia stores, Vue 3 state patterns. Use when managing client state in Vue applications, choosing between Options/Setup stores, composing stores, or implementing persistence.
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。
NgRx SignalStore patterns for Angular state management. Use when managing client state with Angular Signals, composing store features, handling entities, or integrating RxJS effects.
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。
Redux Toolkit patterns for complex client state. Use when managing enterprise-scale state, needing DevTools, entity normalization, or RTK Query for data fetching.
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。
MobX observable state management patterns with mobx-react-lite. Use when implementing reactive client state with observables, computed values, actions, and the observer HOC.
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。
Frontend specification planning frameworks. Use when a spec touches UI components, forms, client state, or user-facing flows. Covers UI-state completeness (loading, error, empty, success), component boundaries, form validation contracts, state ownership, and measurable UI success criteria.
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 component has a `disabled` state/variant, or when building a compound component that owns a disabled state — inherit/provide it via the shared disabled context so state flows from parent to sub-components.
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。
Phase 2 of the feature-pipeline suite. Use this after /fp-explore has filed issues and printed the M1 stop hook — when you need to turn a set of filed GitHub issues into an approved implementation plan and a draft PR. Triggers on: "plan the fix", "create the branch and PR", "draft the implementation plan", "ready to plan", "fp-plan", "next step after explore", "convert issues to a plan", "plan phase". Reads issueNumbers from state, writes a Problem Statement, opens a feature branch + draft PR, spawns a HEAVIER sub-agent for the numbered plan, and blocks on explicit user approval before writing plan to state. Does NOT write any code — that is /fp-implement.
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。
Extracts structure and indicators from a Windows PE file without executing it: headers, sections, imports/exports, resources, entropy, and embedded strings to infer capability and packing. Activates for requests to statically analyze a PE, EXE, or DLL, or inspect imports and headers.
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。
Complete methodology for computing publication-quality cumulative abnormal returns with proper event-study test statistics, matching the robustness of Kaspereit's eventstudy2 for Stata. Covers dateline construction, event-date mapping, estimation and event windows, thin-trading adjustment, OLS with Theil prediction error correction, abnormal return computation, CAR/CAAR/AAR accumulation, boundary contamination guards, and common tests such as Patell, BMP, Kolari-Pynnonen, generalized sign, Wilcoxon, and GRANK-T. Use when the user mentions abnormal returns, event windows, market-model regressions, CARs, CAAR, AAR, eventstudy2, thin trading, trade-to-trade returns, or event-study test statistics.
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。
Fast sprint status check. Reads the current sprint plan, scans story files for status, and produces a concise progress snapshot with burndown assessment and emerging risks. Run at any time during a sprint for quick situational awareness. Use when user asks 'how is the sprint going', 'sprint update', 'show sprint progress'.
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。
State machine patterns for Unity including hierarchical states, async transitions, and cleanup safety.
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 task needs the judgment of a Bioinformatics Scientist — designing a differential-expression or GWAS analysis with correct multiple-testing correction, calling and triaging variants from NGS data using genotype-likelihood confidence rather than raw allele counts, interpreting a BLAST/DIAMOND homology search, choosing or building a genomics pipeline (aligner, caller, normalization method) for a specific data-generating process, or judging whether a computational-biology analysis's statistical design actually supports the biological claim being made. Distinct from a bioinformatics-technician (executes and QC-gates an established pipeline someone else designed) and a data-scientist (general product/experimentation judgment, not genomics-specific statistics) — this role owns which method and statistical model a genomics question requires, and why.
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。
Discover and characterize regulatory elements (enhancers, promoters, silencers, insulators, super-enhancers) using ENCODE data and the cCRE catalog. Use when the user wants to find candidate regulatory elements, identify active enhancers in a tissue, map promoter states, classify chromatin states with ChromHMM, identify super-enhancers with ROSE, understand the functional validation hierarchy (CRISPR > MPRA > reporter), or characterize non-coding genomic regions. Covers the full workflow from ENCODE cCRE lookup through chromatin state segmentation to functional validation and enhancer-gene linkage. Use this skill for ANY regulatory element discovery, classification, or characterization task.
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。
Identify indexing problems and coverage issues using Google Search Console URL inspection data. Checks up to 20 pages for indexing status, coverage state, robots.txt state, and last crawl date. Use when user says "index issues", "indexing problems", "not indexed", "indexing coverage", or "why is my page not indexed".
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 for hands-on Pulumi CLI work: running deployments, fixing broken stacks, and managing infrastructure state. Handles: recovering from stuck or interrupted `pulumi up` with pending operations, cleaning orphaned resources from state after out-of-band cloud deletions, protecting critical resources from accidental `pulumi destroy`, moving resources between stacks without recreating them, targeting specific resources during deployment, migrating between backends (local file to Pulumi Cloud, S3), stack lifecycle management, state export/import/repair, CI/CD pipeline setup, and importing existing cloud resources. Use this skill — not the language-specific Pulumi skills — whenever the user's question is about operating, troubleshooting, or recovering Pulumi infrastructure rather than writing program code.
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。
Verify statistics and claims in blog posts by fetching cited source URLs and checking if the claimed data actually appears on the page. Extracts all load-bearing claims (statistics, product or policy claims, ranking and comparative claims, named sources), validates cited URLs before fetching, and scores match confidence (exact match 1.0, paraphrase 0.7-0.9, not found 0.0). Flags uncited claims as UNVERIFIED. Use when user says "fact check", "verify statistics", "check sources", "validate claims", "factcheck", "source verification".
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。
Configuring Salesforce Omni-Channel routing from scratch or updating existing routing: enabling Omni-Channel, creating Service Channels, configuring Routing Configurations (queue-based and skills-based), setting up Presence Statuses and Presence Configurations, assigning skills to Service Resources, and defining Skills-Based Routing Rules. Trigger keywords: Omni-Channel setup, routing configuration, queue-based routing, skills-based routing, presence status, service channel, routing rules. NOT for agent capacity units and channel weighting — use architect/omni-channel-capacity-model. NOT for Apex routing via PendingServiceRouting — use apex/omni-channel-custom-routing.
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。
Designing Campaign Hierarchy for program-level ROI tracking, configuring Customizable Campaign Influence (CCI) attribution models, and interpreting multi-touch attribution from MCAE B2B Marketing Analytics. Trigger keywords: campaign ROI, attribution model, campaign hierarchy, first-touch, last-touch, multi-touch, CCI, campaign influence, revenue attribution, campaign member status. NOT for deciding which attribution model and KPIs to adopt before any config - use admin/marketing-reporting-requirements. NOT for MCAE connector setup or the campaign sync that writes Campaign Member records - use admin/mcae-pardot-setup. Also covers: CampaignSettings, enableCampaignInfluence2, enableAutoCampInfluenceDisabled, enableB2bmaCampaignInfluence2, enableAccountsAsCM, CampaignInfluenceModel metadata, isDefaultModel, isModelLocked, recordPreference, AllRecords, RecordsWithAttribution, CampaignInfluence.RevenueShare, ModelType, CampaignMemberStatus IsDefault HasResponded SortOrder, HierarchyActualCost, HierarchyAmountWonOpportunities, TotalNumberofResponses, Opportunity.CampaignId primary campaign source.
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 a task iteratively over a user-specified duration by dispatching subagents. The orchestrator stays strictly linear and time-checked, but each iteration fans out MULTIPLE subagents in parallel over independent units (and those subagents may fan out further). Shared state — a compact progress digest and a growing environment cheatsheet — lives on disk and is passed to every subagent BY REFERENCE, killing the per-subagent rediscovery tax. Every subagent first reads an initialiser preamble that points it at that shared state and makes it write findings back, so the cheatsheet populates itself; role prompts are produced ONCE on the filesystem by a single scaffold command and dispatched by path, never re-typed per dispatch. Subagents persist their results to disk and return only a tiny status, so the orchestrator's context stays small and lasts. The orchestrator classifies the goal as FINITE or OPEN-ENDED: finite lists may finish early; open-ended goals use the full duration, never idle, never manufacture busywork. Use when the user gives a task and a duration and wants it ground out iteratively by subagents over that time.
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。
Maintain SESSION-STATE.md, the durable within-session memory that survives context compaction. Use when a constraint, settled decision, existing-infrastructure (survey) finding, or open thread must persist across a long session so it is not re-derived or re-litigated. Triggers on /state, "remember this for the session", "record this constraint/decision", or after surveying what already exists. For cross-session/personal memory use .claude/memory/ on Claude or native memories on Codex; for repo-derivable facts, do not record at all.
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。