tramalia-cli 0.9.1

Capa repo-first de gobierno y evidencia para desarrollo con múltiples agentes IA (reglas, gates, evidence pack, handoff y auditoría).

🧩 Tramalia

Governance and verifiable evidence for building with multiple AI agents. Repo-first.

Define the project rules, orchestrate collaboration between agents, validate every change, and leave a verifiable record — versioned in the repo.

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Git governs human collaboration; Tramalia governs agentic collaboration. It's the change control + audit trail for when several AI agents work on a real project: shared rules, mandatory validations, and verifiable evidence for every close.

Table of contents

• What is it?
• Definition
• Features
• Quick start
• Usage
• Tramalia alone or with your tools
• How it works
• Comparison with the ecosystem
• Requirements
• Documentation
• Contributing
• License

What is it?

When you work on a project with several AI agents (Claude Code, Codex, Cursor, Antigravity…), each one loses context between sessions, uses its own rules, and leaves no evidence of what it did. Tramalia fixes this by using the repository as the source of truth: it drops a versioned convention that any agent reads, and ensures the work is done in a controlled, traceable and consistent way.

Its focus is not to configure your agents (that's Gentle-AI and the like) nor to be a memory engine (that's Engram). Its focus is to govern the repo: rules, gates, evidence and handoff.

Definition

Tramalia is a repo-first governance and evidence layer for development with multiple AI agents. Its goal is not to configure agents nor to replace memory engines, but to ensure that any agent touching a project works under the same rules, runs validations, documents its decisions, leaves verifiable evidence, and hands off clearly to the next session or reviewer.

It does this by orchestrating external tools instead of reimplementing them.

Features

• Governed close (close) — runs the gates, writes their output into the evidence pack and generates the (linked) handoff in one step; blocks the close if a gate fails (unless a documented exception).
• Audit trail (log) — verifiable history of closes: which task, which gates passed, what evidence.
• TUI dashboard (ui) — terminal panel with Overview, browsable Audit and guided Close (extra [tui], Textual).
• Quality gates — build, test, lint, security, database and UX/UI.
• Complete convention — single AGENTS.md + docs/ai/ 00–11 + specs/ + 13 numbered skills anchored to the workflow + failed attempts + typed handoff.
• Role-based subagents with model routing — .claude/agents/ ships 5 governance roles (planner→opus, executor→inherit, reviewer→opus, documenter→haiku, deep-solver→fable); sync fans them out to other hosts, and close --model records which model closed each task.
• doctor — diagnoses which tools your project needs and how to install them (includes Spec Kit).
• Token saving (interop) — derived context (Repomix) + semantic navigation (Serena).
• Rule fan-out (interop) — propagates AGENTS.md to Cursor/Copilot/… with rulesync.
• MCP façade + optional N2 memory (Engram) — exposes/persists without reinventing.

Quick start

pip install "tramalia-cli[pretty]"   # only requires Python 3.10+
tramalia init                        # generate the convention in your repo
tramalia doctor                      # tells you what else to install

Usage

Commands are designed to be short: close takes the task as a positional argument, and agent/reviewer default from .tramalia/config.json (agents.primary/agents.reviewer). If you omit the task, it's read from .tramalia/current-task.md — so the everyday close is just two words.

Command	What it does	Simple example
menu	looping interactive menu with guided prompts	tramalia menu
ui	TUI dashboard: Overview · Audit · Close (extra [tui])	tramalia ui
init	generate the full convention (AGENTS.md, docs/ai 00-11, specs, 13 skills, 5 subagents)	tramalia init
doctor	diagnose which tools are missing and how to install them	tramalia doctor
detect	detect the stack and applicable gates	tramalia detect
close	close a task: gates → evidence → handoff, with enforcement	tramalia close · tramalia close TASK-001
log	audit trail: task · agent · model · honest status	tramalia log
evidence	create just the evidence pack	tramalia evidence TASK-001
handoff	append just the handover entry	tramalia handoff TASK-001
gates	run the quality gates (via mise)	tramalia gates
context	refresh derived context (token saving)	tramalia context
sync	propagate rules and subagents to other hosts (rulesync)	tramalia sync
skills	clone/update referenced skills from their repos	tramalia skills
update	update everything (mise + skills)	tramalia update
mcp	start the MCP façade (extra [mcp])	tramalia mcp

Advanced flags (overrides): close --task --agent --reviewer --model --allow-fail --engram · init --with-headroom --with-ponytail · sync --to --features. Full reference: Commands.

Tramalia alone or with your tools

The governance core works standalone, with Python only: init, doctor, close, log, evidence, handoff and the rules/docs/ai. It needs nothing else to govern the repo.

External tools are optional interoperability, not requirements: mise (runs the gates), Repomix/Serena/codebase-memory-mcp (context), rulesync (fan-out), Engram (N2 memory), Headroom (compression). If they're missing, Tramalia still governs and records it as a documented exception.

How it works

Three layers:

1. The thin CLI (what you run) — a single face that shells out to the real tools.
2. The convention (what stays in your repo) — AGENTS.md, docs/ai/, mise.toml… The real value.
3. The external tools (updated from their repos) — mise, Serena, Repomix, Semgrep, rulesync, the agents.

Comparison with the ecosystem

They don't compete head-on; they complement each other. Each occupies a different space:

Project	Role
Gentle-AI	prepares the agent ecosystem: models, skills, memory, profiles, config
Engram	provides persistent memory across sessions
Headroom	compresses context and outputs to save tokens
Serena · Repomix · codebase-memory-mcp	code intelligence / context (navigation, snapshot, structural graph)
Tramalia	governs the work inside the repo: rules, gates, evidence, handoff, audit and failed attempts

Together: Gentle-AI enables which agents to work with, Engram helps remember, Headroom makes context cheaper, Serena/Repomix/codebase-memory-mcp provide code intelligence, and Tramalia keeps the repo controlled, traceable and consistent. All are optional interop; none touch Tramalia's core (close, log, evidence pack, handoff). Details in the ecosystem page.

Requirements

• Tramalia: only Python 3.10+ (no Node dependencies).
• Recommended: mise, git, uv (bootstrap that installs the rest).
• Node 18+ only if you use sync, the ux gate, or context with Repomix. tramalia doctor flags it as "requires Node".

Documentation

• Site (ES/EN): https://MscottB.github.io/tramalia/ — visual, with diagrams
  • Full example — a real project end to end, showing every option and every third-party tool in action
  • Ecosystem · Full workflow · Architecture · Integrations · Tools
• User manual (Spanish)
• Consolidated design document (Spanish)

Contributing

Contributions are welcome. Read the contributing guide: open an issue to discuss large changes; for small ones, send a PR. Run the tests with pip install -e ".[dev]" && pytest.

License

Apache-2.0 © 2026 Michael Jim Scott Bravo — see LICENSE. Ecosystem license analysis (and why the copyleft of external tools doesn't affect Tramalia): LICENSES.md.