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概要と使いどころ
Coverage-design method for qa-engineer — pyramid ratios per archetype, equivalence/boundary/property case selection, mutation score as the real coverage signal, and a flake-quarantine policy. Turns "coverage is 90%" (a number with no method) into a defensible test plan. Emits TEST-STRATEGY-{slug}.md, which the QA gate checks exists.
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。
Find web sources with query-relevant page excerpts and optional full-page content, and discover workflows, data APIs, and indexes. Use for web research or finding structured records, listings, transcripts, and datasets. Supports semantic tool discovery, domain matching, and progressive catalogue browsing.
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 indexing a code repository into Cognee's code graph or querying it (callers, impact analysis, paths, endpoints) from Antigravity.
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 Antigravity should remember, recall, search, improve, or forget information using Cognee.
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 configuring the Cognee connection, checking whether Cognee is ready or connected, or diagnosing a local or cloud Cognee instance from Antigravity.
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。
Implements accessibility fixes in code. Use when remediating semantic HTML, ARIA, focus, keyboard support, or screen-reader 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。
Measures entropy, mutual information, KL/JS, bits-per-byte. Use when picking KL direction, comparing cross-tokenizer perplexity, trusting MI estimates, or semantic-entropy gating.
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。
PID/MPC/Kalman/anti-windup control primitives for feedback loops. Use when an autoscaler flaps, a controller overshoots after saturation, or budget pacing overspends at peak.
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。
Designs provider runtimes for coding agents. Use when modeling model abstraction, streaming semantics, tool-call normalization, retries, or fallback 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。
LLM serving for latency, batching, caching, quantization, and routing. Use when tuning vLLM or SGLang, sizing KV cache, adding speculative decoding, or cutting serving cost.
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。
Evidence-driven web and open-source research for questions that require multiple sources, factual verification, comparisons, or an adopt/adapt/build decision. Use for substantial research in foreground sessions, the genesis-researcher subagent, and research-profile background sessions. Skip for a single stable fact or a known URL that only needs 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。
Audits an existing rendered interface or frontend diff for hierarchy, content clarity, interaction states, accessibility, responsive behavior, visual consistency, performance-sensitive UI patterns, and anti-generic design defects. Use for a UI/UX review, redesign audit, screenshot review, pre-release visual check, or design-system consistency pass. Not for building a new interface from scratch or for backend-only 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。
Writes a detailed, executable implementation plan from an approved design or multi-step requirement, including exact files, interfaces, tests, commands, checkpoints, and rollback considerations. Use before touching code for a substantial feature, migration, refactor, or cross-cutting change. Not for a one-file bounded fix or for executing a plan that already exists.
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。
Prepares a focused code review request for a branch, commit, pull request, or substantial working-tree diff by defining the review boundary, contract, risk areas, evidence, and questions for an independent reviewer. Use before merge or when another agent needs to review an implementation. Not for processing feedback already received or for claiming runtime correctness.
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。
Simplifies recently changed or explicitly scoped code while preserving observable behavior, error semantics, side effects, ordering, and public contracts. Use for readability cleanup, dead-code removal, reducing nesting, eliminating redundant wrappers, or making an implementation easier to maintain. Not for architecture redesign, new behavior, speculative cleanup, or a refactor without an adequate safety net.
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。
Validates a running application, CLI, API, service, or generated artifact as a user or operator against a prewritten observable behavior contract while remaining source-blind. Use for acceptance checks, runtime proof, anti-fake probes, release smoke tests, or an independent companion to code review. Not for source-quality findings, root-cause diagnosis, or visual design judgment outside the 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。
Tests a real web user flow with a browser by asserting semantic behavior, network and loading states, keyboard access, responsive layouts, and stable visual evidence. Use for browser bugs, end-to-end UI behavior, responsive or accessibility checks, and screenshot baselines. Not for static source review without a browser or for backend-only tests.
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 non-deterministic (flaky) tests by reading CI run logs or test result history. Aggregates pass rates per test, identifies intermittent failures, recommends quarantine or fix, and maintains a flaky test registry. Best run during Polish phase or after multiple CI runs.
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。
Analyze a feature or sprint for scope creep by comparing current scope against the original plan. Flags additions, quantifies bloat, and recommends cuts. Use when user says 'any scope creep', 'scope review', 'are we staying in scope'.
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 @aleabitoreddit ("Serenity")'s full mention archive (built by the follow-aleabito skill) to anticipate where her attention is moving and generate candidate ideas in her style. Two modes — (1) RADAR reads the live mention data for attention momentum (which tickers she is heating up on, new entrants, conviction core, theme rotation) via scripts/radar.js; (2) GENERATOR applies her empirically-mined patterns (theme-rotation logic, selection signature, catalyst playbook) to propose her likely next focus. Every candidate is gated through the serenity-method checklist. This is a CANDIDATE GENERATOR + CHECKLIST, never an oracle or buy/sell signal. Trigger on "what is Serenity ramping on / her next pick / aleabito radar / predict her next move / generate ideas like her / 她下一个可能看什么".
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 image-based product search on the 1688 platform. Use an image URL to find visually similar supplier products, returning title, price, minimum order quantity, monthly sales, repurchase rate, trade score, and seller identity. Triggered when users mention 1688 image search, 1688 visual search, find supplier by image, reverse image search 1688, 1688 product sourcing by image, or Alibaba 1688 image search. Even if the user does not explicitly mention "image search," this skill should be triggered whenever a user provides an image URL and wants to find matching or similar products on the 1688 wholesale platform.
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。
Hybrid search — BM25 keyword + dense vector fused with Reciprocal Rank Fusion. Use when queries have specific identifiers, code symbols, or proper nouns that pure semantic search might miss.
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。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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。
Quantifying priority by scoring competing items with ICE/RICE/WSJF/MoSCoW/Cost of Delay/Kano. No code. Use to prioritize features/bugs/initiatives or arbitrate Must vs Should at MVP scoping.
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。