1.1万 件 ・ 関連度順
概要と使いどころ
Drafts structured insurance coverage opinions analyzing duty to defend and duty to indemnify for carriers. Applies eight corners rule, policy exclusion analysis, and state-specific law. Use when a carrier receives a claim or lawsuit, needs a coverage determination, reservation of rights analysis, or defense obligation assessment.
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Quantify cyber risk using FAIR methodology with Monte Carlo simulation, assess control effectiveness against NIST CSF/CIS/ISO 27001 frameworks, evaluate risk appetite alignment, and analyze cyber insurance coverage adequacy. Covers threat landscape mapping, asset valuation, loss event frequency and magnitude estimation, annualized loss expectancy calculation, control gap analysis with ROI ranking, residual risk assessment, and insurance policy gap modeling at 90th/95th/99th percentile loss scenarios. Use when building risk registers, preparing board-level risk dashboards, evaluating security investment priorities, assessing cyber insurance coverage, or auditing any organization's risk quantification maturity per NIST RMF, ISO 27005, or FAIR standards.
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Audit existing security controls and detection coverage — find gaps against MITRE ATT&CK. Use when asked to "audit our detection coverage", "where are our security control gaps", or "check our MITRE coverage".
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Operate the Ryuumonbuchi MCP server for headless Ghidra reverse engineering. Use when driving decompilation, disassembly, patching, type and symbol recovery, memory edits, transactions, and Ghidra project analysis through a Ryuumonbuchi server (stdio or streamable HTTP). Covers the safe read-only-first workflow, session and address discipline, mutation and transaction rules, headless.run, task and error recovery, raw ghidra.call/ghidra.eval/ghidra.script escape hatches, and a sleep/timing-gate bypass recipe.
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Use when reviewing, shipping, or regression-testing a SKILL.md and you hold one or more captured trajectories where that skill was actually loaded. Translates the skill's instructions into behavior constraints, then reports which were EXERCISED (coverage) versus untested, and flags any that were in-scope but VIOLATED (compliance) — a cheap single-trajectory test-adequacy gate. It surfaces untested instructions rather than auto-blocking, and escalates fail-closed only when a violation touches shared repo state, never-surface memory, or self-modification. Complements skill-counterfactual-audit (which measures EFFECT) and skill-causal-curation (which measures contribution); this one asks ADEQUACY. Backed by the agent-skill-coverage metric (arxiv 2606.20659v2). Triggers on skill review, ship gating, and regression-testing a skill against its trajectories.
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封面与标题 A/B：为带货短视频生成多套封面（自动挑选清晰帧或用干净素材图 + 不同标题与版式）和多组标题/文案，导出 3:4 / 9:16 封面文件和对比图，并给出 A/B 测试方法与记录表。Use when the user wants a video cover, 封面, 首图, thumbnail, 标题, 文案, title variants, A/B test covers for 抖音 / 视频号 / 小红书 / TikTok, or wants to improve click-through rate.
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。
Executes a four-phase feature addition workflow (Discovery, Planning, TDD Implementation, Verification) for Python projects. Use when adding a new feature end-to-end — discovering project structure and integration points, drafting a feature spec with MoSCoW-prioritized requirements and BDD acceptance criteria, implementing via test-first TDD cycles, then verifying with ruff lint, ty type checks, and behavior-focused regression and contract coverage.
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Use when starting a new feature, gathering requirements for an unfamiliar domain, refining a vague idea into actionable scope, or when a user request is ambiguous or underspecified. Conducts SAM Stage 1 discovery — structured requirements gathering through user discussion, asking WHO/WHAT/WHEN/WHY and never HOW. Produces the ARTIFACT:DISCOVERY document containing feature requirements, NFRs, goals, anti-goals, references, and resolved questions. Supports backlog item self-initialization via a
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Use when the user wants a last30days-style pre-research pass in Deepline: discover the critical public, private, CRM, workflow, social, and web data sources for a research/enrichment job; compare provider coverage; estimate Deepline credit cost; recommend the source plan before building or running the workflow; or build custom language/messaging from buyer, competitor, community, and CRM evidence. Triggers: pre-research, source discovery, provider strategy, research data sources, ScrapeCreators, X/Twitter data, Reddit comments, public and private datasets, CRM data, workflow data, custom language, messaging language, pain language.
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Deprecated alias. This skill was renamed to `deepline-scoring`. Use when a user or script still invokes `/niche-signal-discovery`: immediately load and follow the `deepline-scoring` skill instead. Triggers: ICP analysis, niche signals, won vs lost analysis, differential signals, signal discovery, ICP signal report, account scoring signals, lead scoring, first-party signals, buyer signals.
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Разговор-распаковка неудовлетворённостей (discovery-стратегирование). Сократический разбор сырой рефлексии и заметок на триаду Проблема/Неудовлетворённость/Эмоция → состояние пилота → приоритеты месяца (WHAT/WHY). Роль R1 Стратег, метод DP.METHOD.053. Триггеры — «разбери неудовлетворённости», «помоги со стратегией месяца», «что для меня сейчас важно», «/discovery-session».
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 agent configuration coverage across hierarchy levels and phases. Use to ensure complete agent system coverage.
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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for malware configuration recovery, staged payload boundaries, beacon parameter extraction, and IOC decoding. Use when the user asks to recover a malware config, decode C2 or beacon fields, unpack staged payloads, extract bot or campaign IDs, or tie recovered config to observed protocol behavior under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for source maps, build manifests, chunk registries, emitted bundles, obfuscated loader flow, and frontend runtime recovery. Use when the user asks to reconstruct served JavaScript structure, inspect source maps or chunk maps, trace bundle loading, recover hidden routes or APIs from emitted assets, or explain runtime behavior from built frontend artifacts. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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Use when Codex is already in the finding-discovery phase of a security scan or the user explicitly asks to discover candidate security findings in a repository or code change. Do not use as the primary trigger for full PR, commit, branch, patch, or repository scans.
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Write focused tdmcp tests for one assigned coverage gap. Use for Vitest/msw unit tests, integration tests, bridge tests, CLI/config/resource tests, and regression tests that should raise coverage without weakening behavior.
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Builds default probability and recovery rate models with industry data, structural analysis, and loss-given-default estimation. Use when modeling credit losses, estimating recovery values, or analyzing default scenarios.
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Builds recovery waterfall models with absolute priority, secured vs unsecured claims, and plan of reorganization distribution analysis. Use when modeling bankruptcy recoveries, analyzing claim priorities, or estimating creditor distributions.
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。
Workflow recovery protocol for resuming workflows after context loss, session interruption, or errors. Handles state reconstruction, artifact recovery, and seamless workflow continuation.
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Detect missing docs, undocumented files, project health issues, and coverage gaps on session start or on-demand. Scans for README gaps, TODO/FIXME counts, and test coverage holes.
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Implement regenerative recovery using triage, scaffolding, and progressive rebuild. Covers damage assessment, wound classification, emergency stabilization, scar tissue management, and resilience strengthening for systems that have sustained structural damage. Use when a system has suffered an incident needing structured recovery, when a failed transformation left the system in a damaged intermediate state, when accumulated technical debt has caused partial failure, or when a system is functional but degraded and the degradation is worsening.
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Assess and improve garden soil through testing, amendment, composting, and biodynamic preparations. Covers jar test, spade test, earthworm count, amendment by soil type (clay, sandy, depleted, compacted), composting methods (hot, cold, vermicomposting), no-till practices, cover cropping, and biodynamic preparations 500-508. Use when starting a new garden bed, when plants underperform despite adequate water and light, when transitioning to organic or biodynamic practice, when soil has become compacted or depleted, or when building a composting system.
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Preserve and conserve library and archival materials. Covers environmental controls (temperature, humidity, light), handling procedures, book repair techniques (torn pages, loose spines, foxing), acid-free storage, digitization for preservation, and disaster recovery planning. Use when establishing preservation practices for a new or existing collection, when materials show signs of deterioration, when setting up environmental controls for storage, when planning digitization to preserve fragile originals, or when creating a disaster recovery plan for a library or archive.
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Plan a multi-stop tour route with waypoint optimization, drive/walk time estimation, and POI discovery along the route using OSM data. Covers geocoding, nearest-neighbor and TSP-based ordering, time/distance matrix calculation, and itinerary generation with points of interest. Use when planning a road trip or walking tour with multiple destinations, optimizing visit order to minimize travel time, discovering sites along a route, or comparing driving versus walking versus public transport options.
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。