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概要と使いどころ
Assesses scaling companies with product-market fit validation, unit economics maturity, and growth trajectory sustainability analysis. Use when evaluating growth-stage investments, analyzing scaling businesses, or assessing expansion readiness.
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Evaluates 363 sale processes with stalking horse protections, bid procedures, and credit bidding mechanics. Use when analyzing 363 sales, structuring stalking horse bids, or evaluating asset sale alternatives.
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Assesses underlying asset pools with stratification, concentration analysis, historical performance, and credit quality distribution. Use when analyzing collateral pools, stratifying asset characteristics, or evaluating pool quality.
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Values infrastructure assets with DCF, regulated asset base, and comparable transaction methodologies adjusted for regulatory and contractual frameworks. Use when valuing infrastructure assets, analyzing regulated utilities, or benchmarking infra transactions.
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Evaluates asset retirement and decommissioning liabilities with cost estimation, timing analysis, and funding adequacy assessment. Use when analyzing decommissioning costs, evaluating ARO exposure, or assessing abandonment liability.
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Perform a Computer Systems Validation (CSV) assessment following GAMP 5 methodology. Covers user requirements, risk assessment, IQ/OQ/PQ planning, traceability matrix creation, and validation summary reporting. Use when a new computerized system is being introduced in a GxP environment, when an existing validated system is undergoing significant change, when periodic revalidation is required, or when a regulatory inspection demands a validation gap analysis.
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AI self-healing through systematic subsystem assessment, rebalancing, and integration. Maps healing modalities to AI-internal processes: memory foundation, reasoning clarity, tool use accuracy, communication alignment, and creative coherence. Covers assessment triage, subsystem scanning, drift correction, and memory integration. Use mid-session when responses feel formulaic or disconnected, after a chain of errors suggesting subsystem drift, when context overload may have staled earlier assumptions, or as proactive maintenance between complex tasks.
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AI context assessment — evaluating problem malleability, mapping structural rigidity versus flexibility, analyzing transformation pressure, and estimating capacity to adapt. Use when a complex task feels stuck and it is unclear whether to push through or pivot, before a significant approach change to assess whether the current reasoning structure can support it, when accumulated workarounds suggest the underlying approach may be wrong, or as a periodic structural health check during extended multi-step tasks.
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。
xUnit, Moq/NSubstitute, FluentAssertions, and coverlet patterns for any .NET project. Covers test structure ([Fact]/[Theory]/[InlineData]), mocking discipline, fluent assertions, integration test setup with WebApplicationFactory, and coverage measurement. Stack-agnostic — referenced by every .NET plugin in the marketplace. Use this skill to: - Write clear, maintainable unit tests with xUnit [Fact] and [Theory]. - Mock dependencies with Moq or NSubstitute without overusing mocks. - Write expressive assertions with FluentAssertions. - Measure coverage with coverlet and enforce a minimum threshold. Do NOT use this skill for: - ASP.NET Core-specific integration tests (WebApplicationFactory, HttpClient — those are in aspnet-core-plugin:aspnet-conventions). - EF Core in-memory or SQL Server LocalDB test patterns (aspnet-core-plugin:efcore-patterns). - C# language idioms — see csharp-foundation:csharp-conventions.
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。
JUnit 5, Mockito, AssertJ, and Testcontainers patterns for any JVM project. Covers test structure, parameterised tests, mocking discipline, fluent assertions, and integration testing with real containers. Stack-agnostic — referenced by every Java plugin in the marketplace. Use this skill to: - Write clear, maintainable unit tests with JUnit 5. - Mock dependencies with Mockito without overusing mocks. - Write expressive assertions with AssertJ. - Spin up real infrastructure (DBs, message brokers) with Testcontainers for integration tests. Do NOT use this skill for: - Spring-specific test slices (@SpringBootTest, @WebMvcTest, @DataJpaTest — those are in spring-boot-plugin skills). - Framework-specific mocking utilities (MockMvc, WebTestClient).
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Use when working with LLVM IR as a user: emitting IR from clang, running opt passes, lowering with llc, reading IR, or finding a missed optimization. Not for writing new passes: use llvm-passes.
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Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text search, nearby search, or autocomplete suggestions; retrieve detailed place information including hours, contacts, and addresses; monitor geographical boundaries with geofences; or track device locations. Covers authentication, SDK integration, and all Amazon Location Service capabilities.
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Three-tier video pipeline: ffmpeg Quick (5s, instant) → ffmpeg Enhanced with Ken Burns (15s, polished) → Remotion Animated (60-90s, production-grade). Takes static slides from Paper MCP or any PNGs and assembles them into platform-ready video. Make sure to use this skill whenever the user has slides, images, or PNGs and wants to turn them into video — even if they just say 'make a video from these', 'animate my slides', 'I have images and need a TikTok', or 'stitch these together'. Also use when they mention ffmpeg video assembly, Remotion-animated slide assembly, Ken Burns effects, or any slides-to-video pipeline. Owns the slides→MP4 assembly pipeline; for writing, debugging, or running `remotion render` on Remotion code itself, see /remotion-best-practices; for screen-recorded product demos, see /marketing-demo. Works with any PNG source — Paper exports, Canva, screenshots, anything.
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Provides guidelines for developing projected Android XR apps for display glasses using the Jetpack Compose Glimmer UI toolkit. This skill covers foundational Glimmer design principles, workflows for implementing Jetpack Compose Glimmer, and interaction models for the glasses form factor. Use this skill to build an Android XR Augmented Experience app with Jetpack Compose Glimmer that adheres to the Glimmer design system for optimized glasses styling.
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Turn repeatable outputs of a one-person company into compounding assets. Use when Codex needs to explain asset-compounding concepts when needed, verify prerequisite outputs, ask one question at a time, present multiple assetization priorities, and write user-confirmed outputs into `opc-doc/`.
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Use when evidence needs grading before anyone reasons from it — the user asks "how reliable is this?", "grade this source", "check this report", "can I trust this article?", "is this corroborated?", or hands over a URL, a pasted report or a Liberty91 event ahead of an ACH or assessment. The Quality of Information Check from the CIA Tradecraft Primer, adapted for vendor and press CTI reporting. Resolves each document to its originating source, splits it into claims, and grades every claim on two written elements, access level (how the source knows) and claim support (what backs the statement), with a stated rationale, using a fixed rubric with hard caps. The grade is not an Admiralty rating. Five outlets citing one vendor report count as one source; anything that cannot be traced to a primary is capped, not guessed. Returns a graded claim table, gaps, a deception screen and JSON. /ach, /threat-assessment and /writing-assessments run it first by default.
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 you need to answer "which attacker techniques do our controls actually stop, and how well?", "what controls should I have for this threat?", or "what telemetry should I collect to detect it?" — joining a customer's or your own security control baseline to ATT&CK techniques using a public, versioned evidence base of 9,545 control-to-technique mappings from six sources. Produces four ranked lists (addressed strongly, addressed weakly, real gaps, and techniques no control anywhere addresses). Use for control gap analysis, security programme prioritisation, board reporting on coverage, or the Resistance Strength side of a FAIR risk assessment. Invoke after /threat-actor-profiling or /lookup-liberty91 has produced a technique list.
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Reverse engineers malware binaries using NSA's Ghidra disassembler and decompiler to understand internal logic, cryptographic routines, C2 protocols, and evasion techniques at the assembly and pseudo-C level. Activates for requests involving malware reverse engineering, disassembly analysis, decompilation, binary analysis, or understanding malware internals.
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。
Unity scene and asset architecture decisions. Additive scene composition, Addressables vs Resources, AssetReference workflow, asset lifecycle coordination, loading screens. DECISION format: WHEN/DECISION/SCAFFOLD/GOTCHA. Based on Unity 6.3 LTS.
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Use when a task needs the judgment of an Engine and Other Machine Assembler — following the specified multi-stage torque sequence for a multi-bolt joint rather than tightening bolts to final value in convenient order, measuring bearing clearance directly rather than confirming free rotation by hand, verifying critical clearances on the actual assembled stack-up rather than trusting individually-in-tolerance components, or testing sub-assemblies before final integration rather than only at final test.
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Assess business impact of a proposed change. Use when the user says "impact assessment", "impact analysis", "what will this change affect", "change impact", "who is impacted", "ripple effects", "downstream impact", "impact mapping", "what breaks if we change this", "readiness for change" - even if they don't explicitly say "impact assessment".
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Assemble a finished piece from human-written fragments via an orchestrated two-loop pipeline - an assembly loop (assembler + cold reviewer) that sequences the fragments into a draft, then a polish loop (polisher + cold reviewer), then frequency analysis and a catalog-deslop pass with a regression gate. Two modes with opposite fidelity contracts - stitch mode preserves the author's exact wording, narrative mode preserves every idea but may rewrite freely. Use when the user says "mosaic", "assemble my fragments", "stitch these notes into a post", or provides a fragments file to turn into a finished piece. For writing from a topic with research, use article-factory; for prose from scratch, use the prose skill.
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。
Drafts a BSA/AML Risk Assessment for U.S. financial institutions per FinCEN, FFIEC, and OCC standards. Evaluates inherent risks (customer, product, geographic, transaction, third-party), control adequacy, and residual risk. Use when preparing annual BSA compliance assessments, post-acquisition integration reviews, or when business changes trigger reassessment under 31 U.S.C. § 5318(h).
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。
AI compliance analysis for EU AI Act, ISO 42001, NIST AI RMF, GDPR, OECD, financial services regulations (SEC, FCA, FINRA, DORA, MiFID II), and other frameworks. Use when asked to generate a compliance checklist for an AI tool or use case, determine if a risk assessment is required, score an AI tool's risk level, identify where an AI tool or use case could run afoul of regulatory requirements, perform a gap analysis, recommend remediation steps, assess a vendor, draft an acceptable use policy, map training requirements, or review jurisdiction-specific AI rules. Triggers on phrases like "compliance checklist", "risk assessment", "risk score", "does this comply", "EU AI Act", "ISO 42001", "NIST AI RMF", "AI governance", "gap analysis", "vendor assessment", "acceptable use policy", "MNPI", "AI training requirements", or any request to evaluate an AI tool or use case for regulatory compliance or risk.
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。