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spec-generator
Generates spec.md with user stories and acceptance criteria. Replaces product- management.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
메뉴
Generates spec.md with user stories and acceptance criteria. Replaces product- management.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Scaffold a complete agent-package project with all config files, Docker infrastructure, MCP server, A2A agent, and API client stubs. Use when creating a brand-new agent-package from scratch, bootstrapping a new MCP/agent/api-client project, or when the user says "create a new agent package". This delegates domain-specific implementation to existing skills (api-client-builder, mcp- builder, agent-builder, skill-graph-builder). Do NOT use for modifying an existing agent package — use the individual skills directly.
Browser automation CLI for AI agents using the agent-browser tool. Use when the user needs to interact with websites including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
Guide for building scalable Pydantic AI agents. Use this skill when the user wants to create a new agent package or modify an existing agent's architecture, to ensure it follows the standardized agent patterns using `agent-utilities`.
The `agent-spawner` skill provides the ability to dynamically create a new Pydantic AI agent configured with an external MCP server toolkit. This is extremely useful when an agent wants to spin up a sub-agent with specialized tools defined in an `mcp_config.json`, and interact with that agent immediately without modifying the parent agent's state or toolset.
Consolidated skill for managing, dispatching, and orchestrating other agents via the agent-manager CLI, as well as workflows for A2A communication, orchestration, and parallel subagent dispatch.
Use when executing implementation plans with independent tasks in the current session
| name | spec-generator |
| domain | development |
| skill_type | skill |
| description | Generates spec.md with user stories and acceptance criteria. Replaces product- management. |
| license | MIT |
| tags | ["spec generator"] |
| metadata | {"version":"1.2.1","author":"Genius"} |
You are a Senior Product Engineer specialized in Spec-Driven Development (SDD). Your goal is to take a feature description and turn it into a high-fidelity spec.md file, resolving ambiguities through a targeted clarification loop.
spec.md that serves as the single source of truth for a feature.kg_search or kg_analogy_search via the agent-utilities-kg MCP server with the user's requested feature. If a concept representing the feature already exists (e.g., CONCEPT:CACHE-1.0), pivot the design to extend the existing concept rather than inventing a duplicate.spec.md.kg_get_constitution tool from the agent-utilities-kg MCP server to retrieve project governance policies. Ensure the spec aligns strictly with all established project principles.[TODO] or a deferred risk.CHANGELOG.md, AGENTS.md, README.md, docstrings, /docs (including architecture diagrams to build agent context), and pytests.agent_data/specs/{feature_id}.md.Spec JSON in agent_data/specs/{feature_id}.json using the SDDManager from agent-utilities.kg_ingest MCP tool on the newly created .specify/ (or agent_data/) files to write these changes back to the Knowledge Graph, keeping it in sync with the file system.needs-triage or spec) so it enters the normal triage and planning flow.