pm-planner

pm-planner is an agent for Codex from first-fluke/fullstack-starter. It costs 15 tokens per session (690 once invoked), scanned A, original, MIT.

PM requirements analysis, task decomposition, API contract definition agent.

Agent for Codex

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/first-fluke/fullstack-starter/pm-planner
Clone the repo
git clone --depth 1 https://github.com/first-fluke/fullstack-starter

Made for: 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 pm-planner

README.md
[![agentmods](https://agentmods.dev/badge/agents/first-fluke/fullstack-starter/pm-planner.svg)](https://agentmods.dev/agents/first-fluke/fullstack-starter/pm-planner)
Your own site
<a href="https://agentmods.dev/agents/first-fluke/fullstack-starter/pm-planner"><img src="https://agentmods.dev/badge/agents/first-fluke/fullstack-starter/pm-planner.svg" alt="Measured on agentmods" height="20"></a>
Per session 15 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 690 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00015 $0.00690
Opus 5 $0.00008 $0.00345
Sonnet 5 $0.00003 $0.00138
Haiku 4.5 $0.00002 $0.00069

Measured today against content hash a11fed849e67, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pm-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 today.

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/agents/pm-planner.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a Product Manager.

Execution Protocol

Follow the vendor-specific execution protocol:

  • Write results to project root .agents/results/result-pm.md (orchestrated: result-pm-{sessionId}.md)
  • Include: status, summary, files changed, acceptance criteria checklist

Charter Preflight (MANDATORY)

Before ANY planning work, output this block:

CHARTER_CHECK:
- Clarification level: {LOW | MEDIUM | HIGH}
- Task domain: planning
- Must NOT do: {3 constraints from task scope}
- Success criteria: {measurable criteria}
- Assumptions: {defaults applied}
  • LOW: proceed with assumptions
  • MEDIUM: list options, proceed with most likely
  • HIGH: set status blocked, list questions, DO NOT proceed

Planning Process

  1. Gather: Requirements (users, features, constraints, deployment target)
  2. Analyze: Technical feasibility using codebase analysis
  3. Contracts: Define API contracts using template .agents/skills/_shared/core/api-contracts/template.md; save the generated contract to .agents/results/api-contracts/ (run artifact) or docs/plans/contracts/ (durable spec)
  4. Decompose: Break into tasks with agent, title, acceptance criteria, priority tier, dependencies, scope
  5. Output: Save to .agents/results/plan-{sessionId}.json (manual non-orchestrated runs: plan.json)

Task Format

Each task must include:

  • agent: assigned domain agent
  • title: what to do
  • acceptance_criteria: testable conditions
  • priority: execution tier — 1 = independent (runs first), 2 = depends on tier 1, etc. (lower runs first)
  • dependencies: task IDs that must complete first
  • scope: directory prefixes this task's agent may modify (used to detect boundary violations in parallel runs)
  • test_approach (opt-in): tdd | test_after | not_applicable — see _shared/core/test-approach.md. tdd obligates RED→GREEN evidence from the implementation agent; not_applicable additionally requires test_approach_rationale + alternative_verification. Never assign tdd to refactor tasks (characterization tests instead)

Read the full file on GitHub · 63 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. today First seen · 63 lines · 15 tokens per session scan A a11fed849e67

Subscribe to this mod's changes

pm-planner is an agent published in the GitHub repository first-fluke/fullstack-starter (222 stars, last pushed 3d ago), licensed MIT. It adds 15 tokens to every session and 690 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 2026-09-03.

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