vectl — execution control plane for AI agents

中文文档 | Read the Introduction

Structure agents. Enforce discipline.

uvx vectl --help

Markdown Can't Control Your Agent

A 200-step plan in TODO.md. You expect the agent to follow the order, check off completed items, and never skip ahead.

In practice? Agents treat TODO.md as a suggestion, not a rule. They skip steps, forget to mark things done, or get lost in a 1000-line plan and redo work that's already finished. The more you try to hint at structure with comments, bold text, and separators, the worse it gets — because Markdown is just natural language text, and agents have zero obligation to obey it.

The core problem: TODO.md is advice, not enforcement. You can't force an agent to claim a step before starting, or submit evidence before marking it complete.

This is a structural defect in Markdown, not a flaw in your agent:

• No enforcement: you can't prevent agents from skipping steps or require proof of completion
• No dependencies: "Deploy DB" before "Config App" — the agent can only guess the ordering, and nothing stops it from guessing wrong
• Multi-agent conflicts: multiple agents online with no coordination — they can't tell which steps are parallelizable, and simultaneous edits silently overwrite each other
• Completion by self-declaration: the agent says "Done" and that's it — you can't require it to prove tests actually passed

These problems are tolerable at 10-20 steps. At hundreds of steps with multiple agents, TODO.md falls apart completely.

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

Control Plane, Not a Framework

Agent frameworks manage how agents think. vectl manages what agents see, when they see it, and what they must prove.

Capability	Problem Solved	Mechanism
DAG Enforcement	Agents skip dependencies, guess ordering	Blocked steps are invisible — agents literally cannot claim them
Evidence Required	Agent says "Fixed" and moves on	evidence_template forces fill-in-the-blank proof: command, output, PR link
Safe Parallelism	Multiple agents step on each other	claim locking + CAS atomic writes
Auto-Dispatch	Someone must watch and assign tasks	next computes all unblocked steps and sorts them; rejected steps float to top
Token Budget	Agent re-reads hundreds of completed lines	Hard limits across the board: next ≤3, context ≤120 chars, evidence ≤900 chars
Context Compaction	Long conversations cause agent amnesia	checkpoint generates a deterministic JSON snapshot — inject into new session for instant recovery
Handoff Notes	Agents lose state between hosts/sessions	clipboard-write/read/clear stores short notes in plan.yaml (with TTL)
Agent Affinity	Different agents are good at different tasks	Steps can suggest an agent; next sorts by affinity

Quick Start

1. Initialize

uvx vectl init --project my-project

Creates plan.yaml and appends a vectl section to the agent instruction file (CLAUDE.md or AGENTS.md). If the file already exists, your existing content is preserved — vectl only adds its own section.

Commit plan.yaml + AGENTS.md/CLAUDE.md together. The plan is the state machine; the instructions file is the agent entry point.

2. Connect Your Agent

Recommended: connect via MCP for structured tool access.

⚡ MCP (recommended)

{
  "mcpServers": {
    "vectl": {
      "command": "uvx",
      "args": ["vectl", "mcp"]
    }
  }
}

vectl exposes 20 MCP tools. Agents call vectl_status, vectl_claim, vectl_complete, vectl_decide, etc. directly — structured data in, structured data out.

For OpenCode, add to your opencode.jsonc:

{
  "mcp": {
    "vectl": {
      "type": "local",
      "command": ["uvx", "vectl", "mcp"]
    }
  }
}

See OpenCode MCP docs for details.

⌨️ CLI (no MCP)

No setup needed — agents call uvx vectl ... directly. Works everywhere, but agents must parse text output instead of structured data.

uvx vectl init already creates/updates the agent instructions file. To update later: uvx vectl agents-md (use --target claude if needed).

Agent Instruction Files

vectl init and vectl agents-md manage the agent instruction file in your repo.

That file is the entry point for agents: it points to uvx vectl guide topics and sets the rules (one claimed step at a time, evidence required, don't guess specs).

uvx vectl agents-md                 # Update AGENTS.md / CLAUDE.md with vectl section
uvx vectl agents-md --target claude # Force CLAUDE.md

3. Write the Plan

Tell your agent what you need — it will generate and modify the plan through vectl's mutate tool. Do not hand-edit plan.yaml or let agents edit it directly — all modifications must go through vectl tools to ensure validation, lock recalculation, and concurrency safety.

4. 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.

5. Monitor Progress

As a user, your main job is to review progress and make decisions:

uvx vectl top              # Live terminal progress panel (auto-updates on plan changes)
uvx vectl render           # Markdown progress report
uvx vectl dashboard --open # Visual HTML dashboard (static, no server)

vectl top is the lightweight terminal view for keeping a panel open while agents work. It watches the plan files and redraws only when the plan changes, so it avoids high-frequency repainting. To stay readable in normal terminal panes, it automatically folds earlier completed phases, keeps the latest and not-done phases visible, and exits with q or Ctrl-C.

The dashboard includes progress overview, phase status, and DAG dependency graphs. Open in any browser — no server required. The DAG view loads Mermaid.js from a CDN (network required for that tab).

Everything else is in the guide:

• Architect protocol: uvx vectl guide --on planning
• Getting unstuck: uvx vectl guide --on stuck
• Review / validation: uvx vectl guide --on review
• Migration: uvx vectl guide --on migration

Handoffs: Clipboard (Notes) vs Checkpoint (State)

If you're switching agent hosts (Claude Code ↔ OpenCode ↔ Claude Desktop) or handing work between agents, use both:

• Clipboard: short, human-readable notes that live in plan.yaml (with TTL).
• Checkpoint: compact, machine-readable state snapshot for context injection.

Clipboard (recommended for handoffs)

Use this when you want to pass actionable notes between agent hosts/sessions without creating extra files.

Example: Claude Code did a detailed code review, found a few small issues, and you want OpenCode to patch them. Drop the review notes into the clipboard — the other agent reads and applies.

uvx vectl clipboard-write \
  --author "claude-code" \
  --summary "Code review: small fixes" \
  --content "
Target: src/foo.py

Issues:
- Rename X to Y (see comment in function bar)
- Add missing test for edge case Z
- Run: uv run pytest tests/test_foo.py
"

uvx vectl clipboard-read
uvx vectl clipboard-clear

MCP equivalent:

vectl_clipboard(action="write", author="claude-code", summary="Code review: small fixes", content="...")
vectl_clipboard(action="read")
vectl_clipboard(action="clear")

Checkpoint

uvx vectl checkpoint

Paste the JSON into the next session's system prompt.

Data Model (plan.yaml)

version: 1
project: my-project
phases:
  - id: auth
    name: Auth Module
    context: |
      All auth steps must follow OWASP guidelines.
      Test with both valid and malformed JWTs.
    depends_on: [core]
    steps:
      - id: auth.user-model
        name: User Model
        status: claimed
        claimed_by: engineer-1

A YAML file. In your git repo.

No database. No SaaS. git blame it. Review it in PRs. git diff it.

Phase Context: Set context on a phase to give agents guidance that applies to all steps within it. When an agent runs vectl show <step> or vectl claim, phase context appears automatically in the output.

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

Checklist Updates: Human Toggle vs Deterministic Receipts

vectl supports two separate checklist update paths:

1. Legacy human keyword toggle — for interactive use:

   uvx vectl check STEP_ID KEYWORD

   The keyword path does a case-insensitive human match, toggles the matched item, prints Updated checklist: <step>, and points follow-up review at vectl show <step>. It does not use item IDs, revisions, or a target checked value.

2. Deterministic inventory/mutation — for orchestrators and automation:

   uvx vectl check-inventory STEP_ID --json
   uvx vectl check STEP_ID \
     --revision <checklist_inventory_revision> \
     --item-id <item_id> \
     --checked true \
     --json

   check-inventory --json returns parseable JSON with checklist_inventory_revision, items, and each item's item_id, field, index, text, and checked values. Deterministic mutation changes only the - [ ] / - [x] marker for the exact item; surrounding text and ordering are preserved.

First-version deterministic checklist support is intentionally limited to the description and verification step fields. evidence_template checklists are deferred/unsupported for deterministic inventory and mutation.

The revision is scoped to the current checklist inventory for the supported fields. If the revision is stale, deterministic mutation fails without changing state and returns a structured stale_revision error with retry action refresh_inventory.

Batch deterministic mutation is also supported and is all-or-nothing:

uvx vectl check STEP_ID \
  --revision <checklist_inventory_revision> \
  --batch '[{"item_id":"description:0:<hash>","checked":true}]' \
  --json

Any stale, invalid, unsupported, or ambiguous selector prevents partial mutation and returns structured diagnostics. Machine-readable CLI JSON is emitted without Rich/ANSI styling.

MCP exposes the same deterministic fields through vectl_check: use inventory=true to read inventory, or pass revision plus either item_id or field/index with boolean checked to mutate. Batch MCP calls use requests.

Worker/orchestrator receipt flow

In orchestrated work, the orchestrator owns actual checklist mutation. Workers must not call vectl checklist tools or perform natural-language fuzzy mapping. Instead, workers return exact receipts using item IDs and the inventory revision they were given:

checklist_receipt:
  - item_id: "description:0:<hash>"
    revision: "<checklist_inventory_revision>"
    checked: true

The orchestrator validates the receipt schema, refreshes current inventory when needed, rejects stale receipt revisions, and applies only valid item-id/revision requests.

Lock Consistency

Lock status is automatically maintained — agents do not need to manage it. After any write operation (claim, complete, mutate, etc.), vectl recalculates lock status automatically. When a recalculation changes a phase's lock state, vectl emits an informational message:

[vectl] Lock status updated: phase-a (pending)

If you edit plan.yaml directly (outside of vectl commands), run uvx vectl recalc-lock to manually diagnose and repair any lock inconsistencies.

Claim Recovery (Ghost Claims & Split-Brain)

When claim state diverges from plan state, you may encounter errors like:

Step 'foo.bar' is already claimed on branch 'main'

But vectl show foo.bar shows it unclaimed — or shows a different owner. This is a ghost claim or split-brain state.

Symptom Recognition

Symptom	Likely Cause
Claim rejected, show says unclaimed	Ghost claim in claims.json (stale or orphaned entry)
Claim rejected, show shows different owner	Split-brain: claims.json and plan.yaml disagree
status shows claimed, but no agent is working	Stale claim entry (agent crashed/left)

Recovery Commands

# 1. Diagnose: preview what would change (safe, read-only)
uvx vectl repair claims --dry-run

# 2. Diagnose with JSON (machine-parseable output)
uvx vectl repair claims --dry-run --json

# 3. Repair all claims on current branch
uvx vectl repair claims

# 4. Repair only a specific step (scoped repair)
uvx vectl repair claims --step foo.bar

# 5. Verify: check status again
uvx vectl status
uvx vectl show <step-id>

Flags Explained

Flag	Purpose
--dry-run	Preview changes without writing. Always run this first.
--step <id>	Repair only this step's claim. Preserves all other claims.
--json	Machine-readable output. Useful for scripting/CI.

Policy

vectl repair claims follows plan precedence:

• plan.yaml is the source of truth for claim-visible state
• For current branch, claims.json is repaired to match plan step status/owner
• Out-of-scope entries (other branches, unrelated steps) are preserved

When Repo is Healthy (No-Op)

If the repo is consistent, --dry-run shows:

Policy: plan_precedence: ...
changed: false
actions: []

This means claims.json matches plan.yaml — no repair needed.

Anima-Style Example

# You try to claim but get rejected
$ uvx vectl claim auth.user-model
Error: Step 'auth.user-model' is already claimed on branch 'main'

# But status shows something different
$ uvx vectl show auth.user-model
status: pending
claimed_by: null

Recovery:

# Preview the fix
$ uvx vectl repair claims --dry-run --json
{
  "changed": true,
  "actions": [
    {"action": "remove", "key": "main:auth.user-model", "reason": "ghost_claim_or_non_claimed_step"}
  ]
}

# Apply the fix
$ uvx vectl repair claims
[vectl] Repair claims (main)
  removed: main:auth.user-model

# Now claim works
$ uvx vectl claim auth.user-model

Post-Repair Verification

After running repair, always verify:

uvx vectl status              # Confirm expected claim state
uvx vectl show <step-id>      # Check specific step
uvx vectl repair claims --dry-run  # Should now show no changes

---

Technical Details

Architecture, CAS safety, and test coverage (Hypothesis state machine verification): docs/DESIGN.md.