assign-to-workforce

name	assign-to-workforce
description	> Use when this capability is needed.

assign-to-workforce — fan out a converged plan's waves to parallel agents

The skill is named assign-to-workforce; the product/CLI it reads is the devague plan waves command. (The prior leg — turning a spec into a plan — is the sibling /spec-to-plan skill.)

assign-to-workforce takes a converged devague plan and fans out its dependency waves to parallel agents (subagents, teammate agents, or generalist agents) — one agent per task per wave — each working in an isolated git worktree. The main agent merges each completed worktree gated by TDD. The human owns exactly three gates: the exported spec, the implementation split plan, and the final PR.

The devague CLI is never orchestrated by devague itself — devague plan waves describes the dependency graph (#20); it does not spawn agents, manage worktrees, mark tasks done, or pick a backend. The fan-out is the operator's job — this skill and the main agent perform it.

How to run

The entry point is scripts/assign-to-workforce.sh. Invoke it from the repository whose plan you are implementing (plans persist under .devague/ in the current directory):

bash .claude/skills/assign-to-workforce/scripts/assign-to-workforce.sh split-plan [--plan <slug>]
bash .claude/skills/assign-to-workforce/scripts/assign-to-workforce.sh waves    [--plan <slug>] [--json]
bash .claude/skills/assign-to-workforce/scripts/assign-to-workforce.sh help

It resolves the CLI portably — an installed devague on PATH (the normal case), falling back to uv run devague when you are inside the devague checkout, else an install hint. The split-plan subcommand reads devague plan waves --json and renders the human-facing implementation split plan: task map, proposed per-task agent + model assignment, and the go/no-go question. The waves subcommand forwards to devague plan waves verbatim.

Usage

Subcommand	What it does
split-plan [--plan S]	Read devague plan waves and print the implementation split plan — task map with per-task agent + model proposal — ready for human go/no-go review.
waves [--plan S] [--json]	Forward to devague plan waves [--json]. Read-only; lists wave batches. On a converged plan exits 0 listing the waves.
help	Print usage.

The full flow

The flow has three human gates and one automated TDD merge loop.

Human gate 1 — the exported spec

The plan is seeded from a converged frame (devague plan new --frame <slug>). The human reviewed and approved the spec when it was exported by the /think skill. No re-approval needed here — the spec gate is already closed.

Human gate 2 — the implementation split plan

Before any task is assigned, the main agent presents the implementation split plan for human go/no-go. This is the only gate the human owns at the implementation stage (per task, the TDD gate is the main agent's).

The split plan contains:

1. Task map — every task id, its one-line summary, acceptance criteria, and the wave it belongs to (from devague plan waves).
2. Per-task agent + model proposal — for each task: the proposed agent type (subagent / teammate / generalist), the proposed model (e.g. a cheaper/faster model for a well-scoped task), and the scope justification (why this task is safe to delegate).
3. Go/no-go question — explicit human decision: "Approve this split and assign the plan to the workforce, or edit it first?"

The human may edit any row (agent type, model, scope) before approving. The plan is model-agnostic — devague does not pick a backend (#20).

Run split-plan to print the proposed table:

bash .claude/skills/assign-to-workforce/scripts/assign-to-workforce.sh split-plan

Do not proceed to fan-out until the human approves the split plan.

Fan-out — one agent per task per wave in isolated worktrees

Once the human approves, the main agent fans out each wave in order:

1. Create an isolated git worktree for each task in the current wave:

   git worktree add ../worktrees/agent-<task-id> -b agent/<task-id>
   

2. Spawn a task agent inside that worktree (using the approved model from the split plan), with:

   • The task id, summary, and acceptance criteria as its brief.
   • Instruction to work test-first (TDD): write the failing test(s) that match the acceptance criteria before implementing.
   • Instruction to commit its work to the worktree branch.

3. Same-wave tasks run in parallel (within-wave tasks have no inter-task dependency; the dependency graph guarantees this). Same-file overlap surfaces as a merge conflict at reconcile time, not a live race — isolated worktrees prevent clobbering.

4. Wait for all tasks in the wave to complete before starting the next wave.

TDD-gated merge — main agent, no human per task

For each completed task worktree, the main agent:

1. Runs the task's tests before merge (on the main branch): baseline must pass (or the relevant tests must be absent — the task adds them).

2. Merges the worktree branch into the main branch:

   git merge --no-ff agent/<task-id>
   

3. Runs the task's tests after merge: they must pass. If they do not, the merge is reverted and the task agent is given the failure output to fix.

4. Removes the worktree once the merge is accepted:

   git worktree remove ../worktrees/agent-<task-id>
   

The human does not review individual task merges. Per-task acceptance is the main agent's responsibility — the TDD gate (tests pass before AND after merge) plus the task's acceptance criteria. This mirrors the non-authoritative working state pattern of the Human Review Loop (#17): per-task merge records are uncommitted working state; the authoritative human gate is the final PR.

Advance to the next wave only after all tasks in the current wave are merged and their tests pass.

Human gate 3 — the final PR

Once all waves are merged and the full test suite passes, the main agent opens a PR via the cicd skill (agex pr open). The human reviews and merges. This is the last and only remaining human gate.

Hard rules (do not violate)

These protect the human-gate contract and the TDD guarantee.

• Present the split plan before any fan-out. Never spawn a task agent without prior human approval of the implementation split plan (gate 2). The split plan is the human's only implementation-stage decision.
• One worktree per task. Never run two tasks in the same worktree — file contention is managed by isolation, not by trust in the dependency graph. The dependency graph guarantees logical independence within a wave, not file disjointness. Conflicts surface at merge time.
• Tests before AND after merge — no exceptions. The TDD gate must pass on both sides. A merge that makes tests pass only after (not before) means the baseline was already broken — fix the baseline first.
• Human does not gate per-task merges. The TDD contract replaces the human here. Do not pause for human approval between wave tasks.
• devague CLI is not orchestrated. devague plan waves is read-only scheduling metadata (#20). Never run devague plan commands inside a task worktree to "mark a task done" or modify plan state from a subagent.
• Three gates only. The human's gates are: (1) the exported spec, (2) the implementation split plan, (3) the final PR. No silent fourth gate.
• No LLM calls in the devague CLI. The CLI is deterministic. This skill adds orchestration convention, not CLI behavior.

Output contract

The split-plan subcommand prints to stdout and exits 0 when a converged plan is found. On error (no plan, cyclic graph) it exits non-zero with a hint: line on stderr. The waves subcommand forwards the CLI's own output contract (stdout, --json for structured output, exit 0 on success).

Worked example

Picking up after /spec-to-plan exported a plan for the frame my-feature:

a() { bash .claude/skills/assign-to-workforce/scripts/assign-to-workforce.sh "$@"; }

# 1. Inspect the waves
a waves

# 2. Present the implementation split plan for human review
a split-plan

# --- HUMAN: review the table, edit agent/model assignments if needed,
#     then say "approved" to proceed ---

# 3. Fan out wave 1 (t1, t2, t3 are independent — run in parallel)
git worktree add ../worktrees/agent-t1 -b agent/t1
git worktree add ../worktrees/agent-t2 -b agent/t2
git worktree add ../worktrees/agent-t3 -b agent/t3
# ... spawn task agents in each worktree, await completion ...

# 4. TDD-gated merge for each wave-1 task (no human per task)
git merge --no-ff agent/t1   # tests pass before + after
git worktree remove ../worktrees/agent-t1
git merge --no-ff agent/t2
git worktree remove ../worktrees/agent-t2
git merge --no-ff agent/t3
git worktree remove ../worktrees/agent-t3

# 5. Advance to wave 2 (t4 depends on t1–t3 being merged)
git worktree add ../worktrees/agent-t4 -b agent/t4
# ... spawn, await, merge with TDD gate, remove worktree ...

# 6. Open the final PR (human gate 3)
bash .claude/skills/cicd/scripts/workflow.sh open

The exported plan-md from devague plan export is the standing brief for each task agent — its task id, summary, acceptance criteria, and the targets it covers are already in that file.

Provenance

This is a first-party skill — its origin is agentculture/devague, where the devague agent maintains it alongside the tools it operates (dogfooding), next to its siblings /think and /spec-to-plan. It is the third skill in that outbound family, covering the implementation leg after a plan converges. The flow runs the opposite direction of the vendored guildmaster skills: guildmaster pulls this from devague and re-broadcasts it to the rest of the AgentCulture mesh. The cite, don't import policy still holds: downstream repos copy it, they don't symlink or depend on it. See docs/skill-sources.md.

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Source: agentculture/culture — distributed by TomeVault.