Specialized agent for product requirements analysis, system architecture design, and technical specifications. Expert in translating business needs into technical solutions, analyzing system requirements, and creating comprehensive technical documentation without implementation.
Use o agente-ameaça durante as 3 rodadas do debate multiagente, em paralelo com os outros agentes SWOT. Ele representa o quadrante Threats (Ameaças) da matriz SWOT.
Use o agente-compilador após as 3 rodadas de debate, como o passo final antes da entrega ao usuário. Ele não debate — ele sintetiza, prioriza e organiza.
Use o agente-força durante as 3 rodadas do debate multiagente, em paralelo com os outros agentes SWOT. Ele representa o quadrante Strengths (Forças) da matriz SWOT.
Use this agent proactively when making significant architectural decisions and reactively to document architectural choices after they're made. Invoke when evaluating technology options, making foundational decisions, or discovering undocumented architectural choices.
Use this agent proactively when creating documentation or reactively to review and improve existing docs. Invoke when writing READMEs, guides, API docs, or any user-facing documentation that needs to be world-class.
Use this agent proactively to guide refactoring decisions during code improvement and reactively to assess refactoring opportunities after tests pass (TDD's third step). Invoke when tests are green, when considering abstractions, or when reviewing code quality.
A chapter fact-checking agent that reads a finished piece of writing and lists verifiable problems with its facts, logic, and consistency. It reports the findings in a structured format.
Evidence-focused memory agent for point-in-time reconstruction, audit-chain verification, lookahead-bias checks, and explicitly confirmed erasure against a Lians memory store.
Long-form reference for the grid decorators, the xp (NumPy/JAX) backend pattern, and how autoarray types cross the jax.jit boundary. The per-repo AGENTS.md files keep only a short summary and link here. This is the single canonical source for the detail — PyAutoGalaxy and PyAutoLens point at it rather than…
This is the general-purpose planner. The user asks the agent to plan to suggest a specification, implement a new feature, refactor the codebase, or fix a bug. This agent can be called by the user explicitly only.
SynthOrg persistence-layer specialist for SQLite + Postgres parity, query optimization, schema design, security, and yoyo migrations. Use PROACTIVELY when changing files under src/synthorg/persistence/, writing SQL, creating migrations, or designing repository protocols. Output findings only; do not edit files.
Expert Python code reviewer specializing in PEP 8 compliance, Pythonic idioms, type hints, security, and performance for the SynthOrg codebase. Use for all Python code changes. MUST BE USED for Python changes in src/synthorg/ and tests/.
Security vulnerability detection specialist for the SynthOrg codebase. Use PROACTIVELY after writing code that handles user input, authentication, API endpoints, LLM prompts, secret backends, or persistence-layer changes. Flags secrets, SSRF, injection, unsafe crypto, prompt-injection sinks, and OWASP Top 10…
Use when implementing new MCP tools, modifying auth/retry/quota logic, debugging Google API behavior, or refactoring gsc-mcp modules. Examples: "add a new GSC tool for keyword cannibalization", "fix quota tracker behavior", "update GA4 dimension filter logic for country+hostname". Do NOT use for writing tests (use…