Metadata-Version: 2.4
Name: mult-agentes
Version: 1.0.2
Summary: Multi-agent framework with 684 skills, constitutional governance, 19-layer runtime (pipeline, privacy, AI, skills, cognitive, scalability, observability), and Anthropic SDK integration.
Project-URL: Homepage, https://github.com/claudinoinsights/mult-agentes
Project-URL: Documentation, https://github.com/claudinoinsights/mult-agentes#readme
Project-URL: Repository, https://github.com/claudinoinsights/mult-agentes
Project-URL: Issues, https://github.com/claudinoinsights/mult-agentes/issues
Project-URL: Changelog, https://github.com/claudinoinsights/mult-agentes/blob/main/CHANGELOG.md
Author-email: Eric Claudino <eric@claudinoinsights.com>
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Keywords: agents,ai,anthropic,claude,constitutional-ai,llm,multi-agent,orchestration,skills,spec-driven-development
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Description-Content-Type: text/markdown

# mult-agentes

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Multi-agent framework: **Claude Code in VS Code is the executor; the framework is the observability + governance layer.** 684 skills across 39 areas, 7-phase pipeline saga, HMAC-chained audit log, real-time dashboard.

## Install

```bash
pip install mult-agentes                                # core only
pip install "mult-agentes[dashboard,observability]"     # + FastAPI dashboard + OTel
pip install "mult-agentes[dashboard,observability,llm]" # + Anthropic SDK (optional)
```

## Quickstart (60 seconds)

```bash
# 1. Boot the dashboard
make dashboard-real
# → http://localhost:8000 (green banner = connected)

# 2. Register work (replace with whatever you're building)
python -m src.bridge.cli start \
    --intent build_feature --specialist frontend-specialist \
    --description "Implementar autenticação JWT no FastAPI"
# → {"capsule_id": "cap_abc123", ...}

# 3. Record artifacts as you produce them
python -m src.bridge.cli artifact --capsule cap_abc123 --path src/auth.py

# 4. Finalize
python -m src.bridge.cli complete --capsule cap_abc123 --status success \
    --summary "JWT auth shipped + 12 tests passing"
```

The dashboard updates in real time via WebSocket. No Anthropic API key needed — Claude in your VS Code chat is the LLM.

## Architecture in one sentence

```
You (humano) ⇄ Claude Code (VS Code) ⇄ src.bridge.Recorder ⇄ EventBus + WorldState + Audit + Memory ⇄ Dashboard
```

See [`docs/explanation/architecture.md`](docs/explanation/architecture.md) for the full Mermaid diagrams.

## What this repo holds

## What's inside

Three layers of metadata over a flat collection of [agent skills](https://skills.sh):

1. **Skills** — 684 individual `SKILL.md` files installed under `<area>/.agents/skills/<name>/`, each with YAML frontmatter (`name`, `description`, optional `metadata`, `source_org`, etc.)
2. **Curated tier** — 127 hand-selected skills with marketplace install counts and `tier` classification (`docs/reference/registries/_skills-registry.yaml`)
3. **Capability graph + agents/orchestrators** — taxonomy of sub-areas, declarative routing, and the multi-agent hierarchy

The 39 area folders (`ai-ml`, `frontend`, `backend`, `cyber-segurança`, …) are mapped 1:1 to capability domains in the routing compass.

## Documentation

Docs follow the **Diátaxis** framework:

- 📘 [**Tutorials**](docs/tutorials/) — step-by-step learning
- 🛠️ [**How-to guides**](docs/how-to/) — goal-oriented recipes
- 📖 [**Reference**](docs/reference/) — canonical specs, templates, contracts, registries, policies
- 💡 [**Explanation**](docs/explanation/) — architecture, constitution, ADRs

Local docs portal: `make docs-serve` → http://localhost:8000

## Implementation maturity

This repo implements a **subset** of the multi-agent framework specified in `GUIA-ARTEFATOS-MULTIAGENT-v2.md` (v3.2.2, **168 artifacts across 19 layers**). Current coverage: **100%** (168/168) — full documental coverage. Camadas 1-6 templated (44 templates including PROJECT-STRUCTURE); Camadas 7-19 specified (122 specs in `docs/reference/specs/`). Runtime implementation for Camadas 7-19 is staged via the ROADMAP.

**v3.2.2 update (2026-05-24)**: new Camada 19 (Escalabilidade + Ciclo de Vida HomoSapiens) with 11 specs, PROJECT-STRUCTURE template in C3, and Regra 35 (Spec antes do código — SDD) added as 21st absolute rule. See `_framework/ARTIFACTS-INVENTORY.md` for the per-artifact gap analysis.

Fully documented today (all 19 Camadas):

- **SKILL-CATALOG** ↔ `docs/reference/registries/_skills-registry.yaml` (127 curated, 4 tiers) + `registry-full.yaml` (684 total)
- **SKILL-TAXONOMY** ↔ `docs/reference/registries/CAPABILITY-GRAPH.yaml` (39 areas × 64 sub_areas)
- **44 canonical templates** in `docs/reference/templates/`
- **122 specs** in `docs/reference/specs/`

## Layout

```
.
├── docs/                              # Diátaxis-organized documentation
│   ├── tutorials/                     # Learn by doing
│   ├── how-to/                        # Recipes
│   ├── reference/
│   │   ├── specs/                     # 122 architecture + behavior specs (Camadas 7-19)
│   │   ├── templates/                 # 44 instance-ready templates (Camadas 1-6)
│   │   ├── contracts/                 # 5 JSON schemas
│   │   ├── registries/                # _skills-registry, registry-full, agents, orchestrators, …
│   │   ├── policies/                  # cost, error-handling, observability
│   │   └── runtime-api/               # Per-module Python API reference
│   └── explanation/                   # Architecture, constitution, ADRs
├── src/                               # Runtime (13 modules)
│   ├── pipeline/                      # 7-phase orchestrator (Camada 7)
│   ├── privacy/                       # PII, RBAC, audit chain (Camada 8)
│   ├── ai/                            # Model mgmt, RAG, memory, circuit breaker (Camada 9)
│   ├── skills/                        # Loader, router, invoker, versioning (Camada 10)
│   └── (meta_learning, agent_expansion, autonomy, growth, body, …)
├── _framework/                        # Instance docs + runtime data
│   ├── ARTIFACTS-INVENTORY.md         # Per-artifact gap analysis
│   ├── PRD.md, ROADMAP.md, BLUEPRINT.md, BUDGET.md, SCOPE.md, …
│   ├── memory/                        # Episodic + semantic memory (JSONL)
│   ├── locks/                         # Resource locks (JSON)
│   └── observability/                 # agent_metrics.jsonl
├── scripts/                           # Audits, registry sync, marketplace fetch (12 scripts)
├── tests/                             # pytest suites (unit + smoke)
├── <area>/                            # 39 area folders × 684 SKILL.md files
├── .githooks/                         # Versioned git hooks (pre-commit)
├── .github/workflows/                 # CI: audit + verify
├── pyproject.toml                     # PEP 621 metadata
├── Makefile                           # make help
├── README.md (this file)
├── CHANGELOG.md, LICENSE, CONTRIBUTING.md, CODE_OF_CONDUCT.md, SECURITY.md
└── mkdocs.yml                         # Docs portal config
```

## Tier model

| Tier         | Installs threshold | Count |
|--------------|--------------------|-------|
| Platinum     | ≥100K OR official Anthropic | 34 |
| Gold         | 10K–100K           | 30    |
| Silver       | 1K–10K (provenance validated) | 33 |
| Bronze       | 100–1K (provenance validated) | 30 |
| Experimental | <100               | (not curated yet) |

Tier section comments and `_meta` counts in `_skills-registry.yaml` are auto-synced by `scripts/sync_registry.py`.

## Quickstart

```bash
git clone https://github.com/claudinoinsights/mult-agentes.git
cd mult-agentes
python -m venv .venv && source .venv/bin/activate     # Windows: .venv\Scripts\activate
pip install -e ".[dev,test,docs]"

# Set up the audit gate
python scripts/setup_hooks.py

# Validate everything (read-only)
make audit       # 5 audits (structural, semantic, paranoid, deep, verify_all)
make test        # pytest + coverage
make docs        # build MkDocs site
```

## Pre-commit hook

Exit codes:

| Code | Meaning |
|------|---------|
| 0 | All checks passed |
| 1 | Structural or semantic issue (commit aborted) |
| 2 | `_meta` drift detected — run `python scripts/sync_registry.py` and re-stage |

Bypass (not recommended): `git commit --no-verify`.

## CI (GitHub Actions)

`.github/workflows/audit.yml` runs the same gate on every push to `main`/`master` and on every PR. Also verifies `registry-full.yaml` is in sync with the filesystem.

Catches commits made with `--no-verify` or by collaborators who haven't run `setup_hooks.py`.

## Adding a skill

```bash
npx skills add <owner/repo@skill> -y
mv .agents/skills/<name> <area>/.agents/skills/<name>
python scripts/sync_registry.py
python scripts/gen_registry_full.py
make audit
```

If promoting to a curated tier, also add an entry under `platinum`/`gold`/`silver`/`bronze` in `docs/reference/registries/_skills-registry.yaml`.

## Multi-agent hierarchy (Layer 1 → Layer 5)

```
Layer 1: Cortex (global orchestrator, haiku-4-5, always on)
Layer 2: Domain orchestrators (10 total: frontend, backend, ai_ml, devops, security, qa,
         finance_trading, integrations, iot, meta — sonnet-4-6, always on)
Layer 3: Task orchestrator (ephemeral, sonnet-4-6, spawned per story)
Layer 4: Specialists (20 total: frontend-specialist, backend-node-specialist, …, planner-opus)
Layer 5: Workers (5 total: code-writer, file-operator, api-caller, test-runner, git-worker)
```

Each agent declares `capabilities`, `preferred_skills`, `budget_default_usd`, and `primary_orchestrator`. See [`docs/explanation/architecture.md`](docs/explanation/architecture.md) for the full mental model.

## Routing flow

1. Cortex classifies user intent (one of 18 classes in `ROUTING-COMPASS.yaml#intent_classification.classes`)
2. Routing rule selects target domain orchestrator (possibly via `classifier_subroutes`)
3. Domain orch decomposes into stories, delegates to Layer 3 task orchestrators
4. Task orch sequences Layer 4 specialists, which invoke skills via Layer 5 workers
5. `auditor-haiku` runs after every artifact for constitutional compliance

See `docs/reference/registries/ROUTING-COMPASS.yaml` for the full intent → orchestrator mapping.

## Zero-bugs rule

Audits run **structural** + **semantic** checks on every commit. Any of these fails the gate:

- YAML/JSON parse errors
- Missing or invalid SKILL.md frontmatter
- Curated entry without a matching SKILL.md on disk
- `primary_area` references a folder that doesn't exist
- `preferred_skills` references a skill name not on disk
- `governs_areas` references a folder that doesn't exist
- `sub_areas` references a sub_area not in `CAPABILITY-GRAPH.yaml`
- `_meta` counts diverge from filesystem reality
- Tier classification doesn't match install threshold (with `official: true` as escape hatch)

To see what's wrong without committing: `make audit`.

## License

[Apache 2.0](LICENSE) © 2026 Eric Claudino
