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Plans with teeth — TODO.md can't say no. vectl can.

Project description

vectl — DAG-enforced todo list for AI agents

中文文档 | Read the Introduction

TODO.md can't say no. vectl can.

PyPI

uvx vectl --help

Why vectl?

Passive Markdown Plans vectl
Token explosion: Agents re-read the entire plan every call — finished steps included next returns only actionable steps
State drift: Multiple agents edit the same file — silent overwrites, stale state ✅ CAS-safe atomic writes — conflicts detected, never silent
No ordering: Agents pick what to work on — dependencies skipped, work duplicated ✅ DAG-enforced execution — blocked steps are invisible
No verification: "Done" = a checkbox ticked, no proof ✅ Evidence required on completion
Context pollution: Completed steps stay in context forever, diluting attention ✅ Agents see only what matters now

Core Philosophy

  1. Active Gating: Agents cannot skip phases or ignore dependencies. The tool enforces the DAG.
  2. Context Efficiency: Agents only see relevant steps (next actionable items), saving tokens.
  3. Atomic State: Updates are CAS-safe file operations. No stale tracker drift.
  4. Affordance-Driven Output: Every command output includes hints for what to do next.
  5. Minimal Tool Calls: The most common workflow (claim → work → complete) requires the fewest possible interactions.

Quick Start

1. Initialize

uvx vectl init --project my-project

This creates plan.yaml and adds a vectl section to your AGENTS.md (creates one if needed).

2. Connect Your Agent

⚡ Claude Desktop / Cursor
{
  "mcpServers": {
    "vectl": {
      "command": "uvx",
      "args": ["vectl", "mcp"],
      "env": { "VECTL_PLAN_PATH": "/absolute/path/to/plan.yaml" }
    }
  }
}
⚡ OpenCode

Add to your opencode.jsonc:

{
  "mcp": {
    "vectl": {
      "type": "local",
      "command": ["uvx", "vectl", "mcp"],
      "environment": { "VECTL_PLAN_PATH": "/absolute/path/to/plan.yaml" }
    }
  }
}

See OpenCode MCP docs for details.

⌨️ CLI Only (no MCP)

No setup needed — agents call uvx vectl ... directly.

Note: uvx vectl init (Step 1) already creates or updates your AGENTS.md with the section below. You only need the manual template if you skipped init.

📋 AGENTS.md template (click to expand)
## Plan Tracking (vectl)

vectl tracks this repo's implementation plan as a structured `plan.yaml`:
what to do next, who claimed it, and what counts as done (with verification evidence).

Full guide: `uvx vectl guide`
Quick view: `uvx vectl status`

### CLI vs MCP
- Source of truth: `plan.yaml` (channel-agnostic).
- If MCP is available (IDE / Claude host), prefer MCP tools for plan operations.
- Otherwise use CLI (`uvx vectl ...`).
- Evidence requirements are identical across CLI and MCP.

### Rules
- One claimed step at a time.
- Evidence is mandatory when completing (commands run + outputs + gaps).
- Spec uncertainty: leave `# SPEC QUESTION: ...` in code, do not guess.

3. Migrate (Optional)

If your project already tracks work in a markdown file, issue tracker, or spreadsheet, tell your agent:

Read the migration guide (via `uvx vectl guide --on migration` or `vectl_guide` MCP tool).
Migrate our existing plan to plan.yaml.
Prefer MCP tools (`vectl_mutate`, `vectl_guide`) over CLI if available.

4. The Workflow

# ORIENT: Where are we?
uvx vectl status                    # Plan-wide progress dashboard

# PICK: What's available?
uvx vectl next                      # Show claimable steps

# CLAIM: I'm working on this.
uvx vectl claim <step-id> --agent me  # Lock step, get full spec

# WORK: (you write code, run tests)

# COMPLETE: I proved it works.
uvx vectl complete <step-id> --evidence "commit abc123, pytest passed"

# REPEAT: What's unlocked now?
uvx vectl next                      # See what the completion unlocked

Every command output ends with hints for the next action:

$ uvx vectl complete auth.user-model -e "commit abc: model + tests"

Completed: auth.user-model

Next available:
  ○ pending  auth.session-token — Session Token  (auth)
  ○ pending  auth.permissions — Permission Model  (auth)

→ vectl claim <id> --agent <name>
→ vectl show <id>

5. Visualization

See the DAG structure (output is Mermaid flowchart text, paste into GitHub/Obsidian to render):

uvx vectl dag              # High-level phase DAG (default)
uvx vectl dag --phase core # Detailed step DAG within a phase

Output example (renders natively in GitHub):

flowchart TD
  core["✓ Core Logic (5/5)"]
  cli["✓ CLI (4/4)"]
  mcp["▶ MCP Server (1/3)"]
  core --> cli
  cli --> mcp

For all 34 commands (plan mutation, review, admin): uvx vectl --help or uvx vectl guide.

Human Oversight

uvx vectl render                    # Export plan as markdown
uvx vectl diff                      # Changes since last commit
uvx vectl log --last 5              # Recent plan mutations

Data Model (plan.yaml)

version: 1
project: my-project
phases:
  - id: auth
    name: Auth Module
    depends_on: [core]
    steps:
      - id: auth.user-model
        name: User Model
        status: claimed
        claimed_by: engineer-1

Full schema, ID rules, and ordering semantics: docs/DESIGN.md.

Technical Details

Architecture, CAS safety, and test coverage: docs/DESIGN.md.

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