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Design REST or GraphQL APIs by defining data relationships, requests, responses, and authentication. Produce OpenAPI specifications, machine-readable API descriptions, with consistent errors, pagination, and versioning plans, then validate contracts using a mock server.
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Create UI-SPEC.md, a document defining interface design decisions for a frontend phase. The skill coordinates UI research and specification checks, using a chosen phase or automatically selecting the next unplanned one.
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Model distributed systems and concurrent algorithms in TLA+ or PlusCal, then check possible states with TLC. Use the results to investigate deadlocks, broken rules, and differences between specifications and implementation code.
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Writes and reviews Lean 4 proofs, machine-checked arguments for mathematics or specifications. Follows Mathlib conventions to organize definitions and lemmas, fill proof gaps, refactor lengthy proofs, and establish automated checks for unproved claims and style.
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Turn Notion product requirements and feature specifications into linked implementation plans and manageable tasks. Extract requirements, flag ambiguities, and keep task status, milestones, blockers, and decisions aligned as work progresses.
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Turn a multi-file development task or technology migration into a specification with acceptance criteria, then launch background implementation and verification. The workflow clarifies missing requirements, reviews the specification, and tracks progress and blockers through linked jobs.
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Turn a Seed specification into GitHub issues for team planning. The skill creates a parent issue and implementation tasks, distributes acceptance criteria across them, and links the tasks in a progress checklist.
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Convert agreed goals, constraints, and success criteria into a Seed specification an agent can execute and verify. A quality review checks consistency and testable outcomes, with any suggested refinements left for the user to approve.
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Collect Amazon product data from ASINs, unique product identifiers, and compare prices, specifications, reviews, and product images. Produce comparison tables and reports that highlight competitive strengths, weaknesses, and potential market opportunities.
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Extract Amazon search results with product titles, prices, ratings, identifiers, and available specifications. Set keywords, brand, page count, and browsing language to gather structured information for market research, competitor comparisons, and product catalog updates.
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Develop a confirmed talk angle and title into a five-act script with speaker notes and timing. Receive a slide-by-slide specification and a completed prompt to paste into Kimi for presentation generation.
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Archive several OpenSpec changes together after reviewing their documents, task completion, and specification conflicts. The agent checks actual code to decide which specification updates to apply, asks for confirmation, and reports successes, skipped changes, and failures.
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Turn an existing conversation and codebase context into a feature specification. Organize user needs, implementation decisions, testing plans, and scope, then publish the specification to the project’s issue tracker with a label marking it ready for agent work.
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Creates a reusable use case specification file that defines the business problem, stakeholders, and measurable success criteria for model customization, as recommended by the AWS Responsible AI Lens. Use as the default first step in any model customization plan. Skip only if the user explicitly declines or already has a use case specification to reuse. Captures problem statement, primary users, and LLM-as-a-Judge success tenets.
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Transforms project briefs into testable specifications with user stories and acceptance criteria. Use after brainstorming, before planning.
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Generate formal specifications including preconditions, postconditions, invariants, and contracts from code or requirements. Use this skill when documenting APIs, creating formal verification annotations, defining function contracts, specifying class invariants, writing design-by-contract code, or preparing code for formal verification. Supports multiple specification languages including JML, ACSL, Dafny, Eiffel contracts, and documentation annotations.
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Automatically simplify and minimize TLA+ specifications by reducing redundant state variables, merging equivalent actions, and minimizing invariants while preserving specified properties. Use when working with TLA+ specifications that need optimization, simplification, or reduction. Triggers when users ask to minimize, reduce, simplify, or optimize TLA+ specs, or when they want to remove redundancy from formal specifications while maintaining semantic equivalence.
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Generate comprehensive test case documentation from test code, test framework output, existing test docs, and source code context. Use when documenting test suites, creating test specifications, generating test coverage reports, onboarding developers to testing practices, or preparing QA documentation. Analyzes test functions (pytest, unittest) to extract test names, docstrings, assertions, and organization, then produces structured markdown with both overview-level summaries and detailed test case specifications including purpose, preconditions, steps, expected results, and test data. Triggers when users ask to document tests, generate test specifications, create test reports, summarize test coverage, or explain what tests do.
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Translate natural-language requirements or structured specification documents into formal temporal logic properties (LTL, CTL, safety/liveness properties). Use when users need to formalize requirements for model checking, formal verification, or property specification. Handles embedded/real-time systems, hardware verification, concurrent systems, and reactive systems. Resolves ambiguities, asks clarifying questions when needed, and outputs machine-checkable formulas with explanations. Supports multiple output formats (SPIN, NuSMV, Uppaal, TLA+, Maude).
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Generate systematic refinement steps from high-level specifications to concrete implementations in Isabelle/HOL or Coq, preserving correctness obligations at each step. Use when working with formal verification, program refinement, proof development, or when translating abstract specifications into executable code while maintaining formal guarantees. Supports data refinement (abstract types → concrete structures), algorithmic refinement (specifications → algorithms), and stepwise refinement with proof obligations.
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Automatically generate TLA+ specifications from program code, repositories, or system implementations. Use when asked to generate TLA+ spec, create TLA+ specification from code, convert program to TLA+, formalize system in TLA+, extract TLA+ model from code, or when working with formal specification of concurrent systems, distributed systems, protocols, algorithms, or state machines that need to be verified.
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Convert pseudocode, algorithm descriptions, or specifications into complete, executable Python code. Handles natural language descriptions, structured pseudocode, and formal algorithm specifications. Generates production-ready code with type hints, docstrings, error handling, and test cases. Use when users need to (1) convert pseudocode to Python, (2) implement algorithms from descriptions, (3) translate algorithm specifications to code, (4) generate Python implementations from textbook pseudocode, or (5) create executable code from high-level algorithm designs.
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Create ACSL (ANSI/ISO C Specification Language) formal annotations for C/C++ programs. Use this skill when working with formal verification, adding function contracts (requires/ensures), loop invariants, assertions, memory safety annotations, or any ACSL specifications. Supports Frama-C verification and generates comprehensive formal specifications for C/C++ code.
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Expert product specification and documentation writer. Use when creating PRDs, user stories, acceptance criteria, technical specifications, API documentation, edge case analysis, design handoff docs, feature flag plans, or success metrics. Covers the full spectrum from high-level requirements to implementation-ready specifications.
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