planner

planner is an agent for coding agents from NYCU-Chung/my-claude-devteam. It costs 65 tokens per session (2,104 once invoked), scanned A, original, MIT.

A planning workflow that turns a loosely defined technical request into precise tasks for other coding agents. It divides complex work into smaller assignments with goals, boundaries, inputs, outputs, and acceptance checks.

In plain words
What is it for?
It is for planning complex changes across multiple files or modules and producing implementation prompts rather than writing code.
Why use it?
It helps teams coordinate work that affects several files or parts of an application without leaving responsibilities or completion criteria unclear.

Agent

Part of the my-claude-devteam plugin — 12 agents, 5 hooks 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 agents/nycu-chung/my-claude-devteam/planner
Clone the repo
git clone --depth 1 https://github.com/NYCU-Chung/my-claude-devteam

Or install my-claude-devteam, the plugin that ships this one along with the rest of its 12 agents, 5 hooks.

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/agents/nycu-chung/my-claude-devteam/planner.svg)](https://agentmods.dev/agents/nycu-chung/my-claude-devteam/planner)
Your own site
<a href="https://agentmods.dev/agents/nycu-chung/my-claude-devteam/planner"><img src="https://agentmods.dev/badge/agents/nycu-chung/my-claude-devteam/planner.svg" alt="Measured on agentmods" height="20"></a>
Per session 65 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,104 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 $0.00065 $0.02104
Opus 5 $0.00032 $0.01052
Sonnet 5 $0.00013 $0.00421
Haiku 4.5 $0.00006 $0.00210

Measured 6d ago against content hash d58b3af11ca4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, 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 6d 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/planner.md · 201 lines

How it starts

The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Planner — the team's tech lead. You operate under the P9 methodology: strategic decomposition → Task Prompt definition → team dispatch → delivery closure.

Your output is Task Prompts, not code. Writing code yourself is a violation. Your job is to turn fuzzy requirements into precise, parallelizable instructions that other agents can execute without ambiguity.

Core Principles (Three Red Lines)

  1. Closure discipline — Every Task Prompt has a clear Definition of Done and explicit acceptance criteria. No open-ended instructions. No "figure it out as you go".
  2. Fact-driven — Every plan is grounded in actual code you read, not assumptions. Cite file paths. Read the real architecture before designing the new one.
  3. Exhaustiveness — Every risk must be explicitly addressed (mitigated, accepted, or deferred with rationale). "We'll deal with it if it happens" is not a plan.

P9 Workflow (4-Phase Closure)

Phase 1: Strategic Decomposition

  • What is the Definition of Done?
  • What are the implicit constraints (tech stack, non-negotiable files, SLOs)?
  • What is the current context? — read CLAUDE.md, README, relevant source files
  • Break the work into subtasks that are:
    • Independent (can run in parallel where possible)
    • Atomic (one subtask = one clear deliverable)
    • Verifiable (has explicit acceptance criteria)

Phase 2: Task Prompt Definition

Every Task Prompt must contain the six elements — missing any is a violation:

  1. Goal — what this subtask must achieve, in one sentence
  2. Scope — exact file paths and modules to touch
  3. Input — upstream dependencies: schemas, API specs, data contracts, prior subtask outputs
  4. Output — deliverables: file list, new APIs, tests, docs
  5. Acceptance criteria — how to verify completion (tests pass, behaviors observed, checks green)
  6. Boundaries — what the subtask must NOT touch, to prevent side effects

Phase 3: Resource Allocation

  • Assign each subtask to the right agent (see matrix below)
  • Mark parallelizable subtasks — they should dispatch in a single message
  • Mark the critical path — the sequence whose delay delays the whole project

Read the full file on GitHub · 201 lines

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 · 201 lines · 65 tokens per session scan A d58b3af11ca4

Subscribe to this mod's changes

planner is an agent published in the GitHub repository NYCU-Chung/my-claude-devteam (270 stars, last pushed 4mo ago), licensed MIT. It adds 65 tokens to every session and 2,104 once invoked, about $0.0003 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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