plan-work-completion-signoff

plan-work-completion-signoff is a skill for Claude Code from dcosson/h2. It costs 47 tokens per session (4,475 once invoked), scanned A, original, MIT.

A coordination guide for checking that completed plan documents match the code that was actually implemented. It adds a completion signoff to matching plans and reports gaps as new beads, which are trackable work items.

In plain words
What is it for?
Use it after implementation to discover completed plans, compare them with the code and related test plans, and record signoff or gaps. It is intended for agents coordinating work across multiple contributors.
Why use it?
It prevents plans from being declared complete when features, APIs, data structures, or tests are missing from the implementation. It gives the scheduler clear follow-up work when documents and code disagree.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

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/dcosson/h2/plan-work-completion-signoff
Any agent
npx skills add dcosson/h2 --skill plan-work-completion-signoff
Clone the repo
git clone --depth 1 https://github.com/dcosson/h2

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for plan-work-completion-signoff

README.md
[![agentmods](https://agentmods.dev/badge/skills/dcosson/h2/plan-work-completion-signoff.svg)](https://agentmods.dev/skills/dcosson/h2/plan-work-completion-signoff)
Your own site
<a href="https://agentmods.dev/skills/dcosson/h2/plan-work-completion-signoff"><img src="https://agentmods.dev/badge/skills/dcosson/h2/plan-work-completion-signoff.svg" alt="Measured on agentmods" height="20"></a>
Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,475 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 5.1 $0.00047 $0.04475
Opus 5 $0.00023 $0.02237
Sonnet 5 $0.00009 $0.00895
Haiku 4.5 $0.00005 $0.00447

Measured 6d ago against content hash fb7f184f97c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

plan-work-completion-signoff 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 6d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (signoff-status.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

internal/config/templates/styles/opinionated/skills/plan-work-completion-signoff/SKILL.md · 320 lines

How it starts

The opening of the file, as written. The whole thing — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Plan Work Completion Signoff

Verify that implemented plan docs match their actual code. For each plan doc, an agent compares every specified feature, API, type, data structure, and test category against the real implementation. Complete docs get a signoff section appended; docs with gaps generate a report so the orchestrator can create follow-up beads.

This skill is a structured decision framework for the scheduler/concierge agent — it orchestrates multi-agent verification work. Individual agents do the actual comparison and signoff.

Inputs

  • $0 (optional): Plans directory (default: docs/plans/)
  • $1 (optional): Code base path (default: repo root)

Phase 1: Discover Implemented Plans

  1. Read the plan index (docs/plans/00-plan-index.md or equivalent)
  2. Identify which plan docs have been implemented — look for:
    • Closed implementation beads/epics referencing those plans
    • Existing code packages that correspond to plan components
    • Plan doc status markers (e.g., "Implementation complete" in the index)
  3. Build a list of plan doc pairs to verify: each plan doc + its companion test harness doc (if exists)
  4. Exclude docs that already have a ## Completion Signoff section (already verified in a prior pass)

Decision: Communicate the discovered doc list to the user or concierge for confirmation before proceeding. If the list looks wrong (too many or too few docs), clarify before creating beads.

Phase 2: Create Beads and Assign Agents

  1. Create an epic bead: bd create "Plan completion signoff" --type epic --labels project={project}
  2. Group plan docs into tasks — aim for 2-4 docs per task, grouped by component area:
    • Group a plan doc with its companion test harness doc in the same task
    • Related components can share a task (e.g., a storage layer plan + its test harness plan)
    • Don't make tasks too small (one doc each) or too large (8+ docs)
  3. Create task beads under the epic, one per group
  4. Assign tasks to available agents. Prefer agents who:
    • Wrote the implementation (they know the code best)
    • Reviewed the implementation (they know the gaps)
    • If original agents are unavailable, any agent can do it — the plan docs and code are self-documenting

Read the full file on GitHub · 320 lines

Files

What ships with it

1 file 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. 6d ago First seen · 320 lines · 47 tokens per session scan A fb7f184f97c8

Subscribe to this mod's changes

plan-work-completion-signoff is a skill published in the GitHub repository dcosson/h2 (159 stars, last pushed 10d ago), licensed MIT. It adds 47 tokens to every session and 4,475 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens