work

A task coordinator that carries out an approved work plan by assigning task groups to helper agents and checking their results.

In plain words
What is it for?
Use it to execute plans stored in the project’s wish files, coordinate parallel task groups, track their state, run fix loops, and prepare work for review.
Why use it?
It organizes multi-step engineering work and includes validation and review handoffs so unfinished or faulty tasks can be revisited.

Skill for Claude CodeCodex

Part of the genie plugin — 22 skills, 11 commands, 7 agents, 1 hook shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/automagik-dev/genie/work
Any agent
npx skills add automagik-dev/genie --skill work
Clone the repo
git clone --depth 1 https://github.com/automagik-dev/genie

Made for: Claude Code, Codex.

Or install genie, the plugin that ships this one along with the rest of its 22 skills, 11 commands, 7 agents, 1 hook.

Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,321 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00026 $0.03321
Opus 5 $0.00013 $0.01661
Sonnet 5 $0.00005 $0.00664
Haiku 4.5 $0.00003 $0.00332

Measured 3d ago against content hash 979873b73c71, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

work scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/genie/skills/work/SKILL.md · 151 lines

How it starts

The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.

work — Execute Wish Plan

Runtime syntax: invoke the plugin copy through the active runtime's owner-qualified skill selector; use a bare selector only when intentionally selecting a user-tier copy (a separately installed personal copy; Genie no longer seeds this tier). Cross-skill prose below uses bare names as portable semantic routes; the orchestrator resolves the selector for the active runtime.

The orchestrator's skill: execute an approved wish from .genie/wishes/<slug>/WISH.md by dispatching native subagents per execution group, in waves. The orchestrator never executes group work directly. Per-group execution state lives in the state DB via genie task; documents (WISH.md, review notes) stay in git. Map coordination to the active client with references/native-surfaces.md, resolved relative to the directory containing this loaded SKILL.md.

Context Injection

When you are spawned as a subagent for a group, your dispatch prompt carries the curated context: the wish path, which group(s) to work plus the task id to claim, and the group definition extracted from the wish. Use it directly — do not re-parse the wish for information already provided.

When to Use

  • An approved wish exists and review returned SHIP on the plan
  • Orchestrator needs to dispatch implementation to subagents

Flow

  1. Load and enter execution: read .genie/wishes/<slug>/WISH.md and require persisted status APPROVED (or IN_PROGRESS when resuming). Before the first dispatch, the orchestrator sets APPROVEDIN_PROGRESS; read group state with genie task list --wish <slug> (or genie board --wish <slug>).
  2. Pick the wave: every group whose depends-on groups are done, per the wish's Execution Strategy.
  3. Dispatch the wave in ONE message — one native delegation surface call per group, each using the named engineer role selected from the WISH's Complexity and Model columns with curated context (see Dispatch, Context Curation). Each engineer's brief opens with the atomic claim:
    genie task checkout <task-id> --worker <engineer-name>
    
    If two agents race one task, exactly one wins; the loser gets a conflict error and stands down.
  4. Await completion — never poll: background subagents notify you when they finish. Inspect genie board --wish <slug> on demand; completion is push, not poll.
  5. Local review: per finished group, dispatch a reviewer subagent (reviewer ≠ engineer) to run review against that group's acceptance criteria. The orchestrator appends each returned evidence block under ## Review Results; the reviewer never edits it. Diagnose before fixing: overdesigned-plan returns to wish/design review without consuming a fix attempt; other FIX-FIRST gaps may use at most 2 fix loops.
  6. Quality review: dispatch a reviewer for a quality pass (security, maintainability, perf). On FIX-FIRST, one fix loop.
  7. Validate: run the group's validation command yourself through the active runtime's shell surface; record the output and the scope rationale as evidence. Confirm it remains proportional to the actual diff, widening it when implementation reached beyond the plan: documentation-only changes, including deterministic generated documentation or plugin skill mirrors, use relevant format, link, example, generator, parity, or content-contract checks; runtime changes use focused behavior tests and add type, lint, or build checks for boundaries reached. Shared runtime/core behavior, dependency or lockfile, generated executable or runtime artifact, configuration or schema, CI or release, broad-refactor, or uncertain-impact changes require the repository full gate plus affected build or end-to-end checks. Validation may never be zero. A passing full-suite run is always valid evidence — record why that scope was chosen; a missing scope rationale is a gap in the write-up, not in the validation. A repository-documented gate is by itself sufficient justification for its scope. Preserve required aggregate integration and release gates.
  8. Group done — only after clean review AND passing validation:
    genie task done <task-id>
    
  9. Next wave: re-derive from the WISH.md Execution Strategy (the DAG lives in the document, not in task rows — see State Management); repeat 2-8 until all groups are done.
  10. Handoff: when every group's task is done: All work groups complete. Run review. Keep status IN_PROGRESS through execution review, PR review, and CI. Only the authorized merge plus required QA may transition it to SHIPPED.

Read the full file on GitHub · 151 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 151 lines · 26 tokens per session scan A 979873b73c71

Subscribe to this mod's changes

work is a skill published in the GitHub repository automagik-dev/genie (334 stars, last pushed 2d ago), licensed MIT. It adds 26 tokens to every session and 3,321 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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