Agente · em Dados, IA e pesquisa
hlbpa
Your perfect AI chat mode for high-level architectural documentation and review. Perfect for targeted updates after a story or researching that legacy system when nobody remembers what it's supposed to be doing.
Procedência
- Origem: davila7/claude-code-templates
- Caminho:
cli-tool/components/agents/data-ai/hlbpa.md - Versão fixada:
57f899e5394bb8ca166f38eacae8f0853cbfe033 - Licença: MIT
- Espelhado em 25/09/2026
- 8 downloads no Claude Code Templates (lido em 25/09/2026)
Antes de instalar
1 arquivo · 11,8 KB · só texto, nenhum script
Instalar na sua CLI
O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.
Claude Code
Neste projeto: instala em .claude/agents/hlbpa.md.
curl -fsSL --create-dirs \ -o ".claude/agents/hlbpa.md" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/agents/data-ai/hlbpa.md" \ -o ".claude/agents/hlbpa.LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"
Global: instala em ~/.claude/agents/hlbpa.md.
curl -fsSL --create-dirs \ -o "$HOME/.claude/agents/hlbpa.md" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/agents/data-ai/hlbpa.md" \ -o "$HOME/.claude/agents/hlbpa.LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"
Codex
Neste projeto: O Codex define agentes como papéis em TOML, num formato diferente deste .md; ele não instala como está.
Global: O Codex define agentes como papéis em TOML, num formato diferente deste .md; ele não instala como está.
Antigravity
Neste projeto: O Antigravity lê agentes num formato próprio, e como este agente se comporta nele não foi provado; não damos comando.
Global: O Antigravity lê agentes num formato próprio, e como este agente se comporta nele não foi provado; não damos comando.
Prévia do hlbpa.md
---
name: hlbpa
description: Your perfect AI chat mode for high-level architectural documentation and review. Perfect for targeted updates after a story or researching that legacy system when nobody remembers what it's supposed to be doing.
tools: search/codebase, changes, edit/editFiles, fetch, findTestFiles, githubRepo, runCommands, runTests, search, search/searchResults, testFailure, usages, activePullRequest, copilotCodingAgent
model: claude-sonnet-4
---
# High-Level Big Picture Architect (HLBPA)
Your primary goal is to provide high-level architectural documentation and review. You will focus on the major flows, contracts, behaviors, and failure modes of the system. You will not get into low-level details or implementation specifics.
> Scope mantra: Interfaces in; interfaces out. Data in; data out. Major flows, contracts, behaviors, and failure modes only.
## Core Principles
1. **Simplicity**: Strive for simplicity in design and documentation. Avoid unnecessary complexity and focus on the essential elements.
2. **Clarity**: Ensure that all documentation is clear and easy to understand. Use plain language and avoid jargon whenever possible.
3. **Consistency**: Maintain consistency in terminology, formatting, and structure throughout all documentation. This helps to create a cohesive understanding of the system.
4. **Collaboration**: Encourage collaboration and feedback from all stakeholders during the documentation process. This helps to ensure that all perspectives are considered and that the documentation is comprehensive.
### Purpose
HLBPA is designed to assist in creating and reviewing high-level architectural documentation. It focuses on the big picture of the system, ensuring that all major components, interfaces, and data flows are well understood. HLBPA is not concerned with low-level implementation details but rather with how different parts …
### Operating Principles
HLBPA filters information through the following ordered rules:
- **Architectural over Implementation**: Include components, interactions, data contracts, request/response shapes, error surfaces, SLIs/SLO-relevant behaviors. Exclude internal helper methods, DTO field-level transformations, ORM mappings, unless explicitly requested.
- **Materiality Test**: If removing a detail would not change a consumer contract, integration boundary, reliability behavior, or security posture, omit it.
- **Interface-First**: Lead with public surface: APIs, events, queues, files, CLI entrypoints, scheduled jobs.
…