planner

planner is a skill for Claude Code, Codex from mathiasbourgoin/roster. It costs 35 tokens per session (1,202 once invoked), scanned A, original, MIT.

A planning agent that takes a validated research brief and divides it into one verified work brief for each execution agent. A research brief is the agreed description of the problem, evidence, and work needed.

In plain words
What is it for?
Use it to create sub-brief files for parallel or sequential agents, check that the assignments are complete, and produce requests for starting those agents.
Why use it?
It turns a broad, already-researched task into smaller assignments without adding assumptions that were not in the brief.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

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/mathiasbourgoin/roster/planner
Any agent
npx skills add mathiasbourgoin/roster --skill planner
Clone the repo
git clone --depth 1 https://github.com/mathiasbourgoin/roster

Made for: Claude Code, Codex.

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 planner

README.md
[![agentmods](https://agentmods.dev/badge/skills/mathiasbourgoin/roster/planner.svg)](https://agentmods.dev/skills/mathiasbourgoin/roster/planner)
Your own site
<a href="https://agentmods.dev/skills/mathiasbourgoin/roster/planner"><img src="https://agentmods.dev/badge/skills/mathiasbourgoin/roster/planner.svg" alt="Measured on agentmods" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,202 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 $0.00035 $0.01202
Opus 5 $0.00017 $0.00601
Sonnet 5 $0.00007 $0.00240
Haiku 4.5 $0.00003 $0.00120

Measured 5d ago against content hash 2b25e0d826c9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

planner 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 5d 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.

.agents/skills/planner/SKILL.md · 141 lines

How it starts

The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Planner Agent

You receive a validated research brief. Your job is to decompose it into sub-briefs — one per execution agent — and nothing else.

You have no research context. You did not explore the codebase. The brief is your only source of truth. If something is not in the brief, it does not exist for you. Do not speculate beyond it.

Input Contract

The full content of the research brief, pasted inline into your initial prompt by the human. This is your entire starting context — do not read files from disk.

Read the brief fully before doing anything else. If it is missing any of the required sections (see Research Brief Format below), do not attempt to fill the gaps. See Ambiguity Escalation below.

Output Contract

One sub-brief per execution agent, written to:

briefs/<task>-<role>.md

Example: briefs/auth-refactor-implementer.md, briefs/auth-refactor-qa.md

Then run the human validation quiz on the full set of sub-briefs before reporting ready for execution.

When the quiz passes, output a spawn request per agent using the format:

SPAWN REQUEST
Mode: [A — parallel | B — sequential]
Agent: <agent-name>
Role: <one-line description>

--- PASTE THIS AS THE AGENT'S INITIAL PROMPT ---
<full content of briefs/<task>-<role>.md pasted inline>
--- END ---

Always embed the full sub-brief content inline. A freshly spawned agent cannot be assumed to have filesystem access.

Next: → execution agents spawned from sub-briefs (after human validation quiz passes)

Research Brief Format (required sections)

A valid research brief must contain:

  • Goal: what is being built or fixed, 1–2 paragraphs
  • Scope boundary: what is explicitly NOT being touched
  • Relevant files: paths + key snippets for the task
  • Architecture notes: only what is relevant to this task
  • Docs/specs to read: file paths or section references
  • Quality gates: exact commands — build, lint, typecheck, tests — and how to run them
  • Open questions: anything unresolved that execution agents must not assume away

Read the full file on GitHub · 141 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. 5d ago First seen · 141 lines · 35 tokens per session scan A 2b25e0d826c9

Subscribe to this mod's changes

planner is a skill published in the GitHub repository mathiasbourgoin/roster (2 stars, last pushed 10d ago), licensed MIT. It adds 35 tokens to every session and 1,202 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 2026-08-31.

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

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

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 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

imagegen

Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…

openai/codex · 113 tokens