gsd-planner

gsd-planner is an agent for Claude Code, Codex from SpillwaveSolutions/agent-brain. It costs 33 tokens per session (11,127 once invoked), scanned A, original, MIT.

A helper agent that turns a software project phase into executable implementation plans. It breaks work into tasks, maps dependencies, uses project decisions, and checks that the plan supports the intended outcome.

In plain words
What is it for?
Use it to create or revise phase plan files, including plans for closing verification gaps or incorporating review feedback.
Why use it?
It gives coding agents clearer instructions for what to build and in what order, reducing ambiguity before implementation starts.

Agent for Claude CodeCodex

Written for Codex and Claude Code: installed under .codex/, but also a Claude Code subagent (agents/*.md). Also seen: reads .claude/ paths; mentions AGENTS.md; mentions Codex.

Not installable: its command points at a path on the author’s own machine, so it runs nowhere else. The line is /Users/richardhightower/clients/spillwave/src/agent-brain/.codex/get-shit-done/bin/gsd-tools.cjs.

Install

Getting it into your agent

There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.

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 gsd-planner

README.md
[![agentmods](https://agentmods.dev/badge/agents/spillwavesolutions/agent-brain/gsd-planner.svg)](https://agentmods.dev/agents/spillwavesolutions/agent-brain/gsd-planner)
Your own site
<a href="https://agentmods.dev/agents/spillwavesolutions/agent-brain/gsd-planner"><img src="https://agentmods.dev/badge/agents/spillwavesolutions/agent-brain/gsd-planner.svg" alt="Measured on agentmods" height="20"></a>
Per session 33 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 11,127 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. 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 $0.00033 $0.11127
Opus 5 $0.00016 $0.05563
Sonnet 5 $0.00007 $0.02225
Haiku 4.5 $0.00003 $0.01113

Measured today against content hash d7f42d2b104e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

gsd-planner scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Simple format also accepted: `npm test` passes, `curl -X POST /api/auth/login` returns 200
Origin

Copies of this mod

6 near-identical copies found in the catalogue:

.codex/agents/gsd-planner.md · 1,354 lines

How it starts

The opening of the file, as written. The whole thing — 1,354 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<codex_agent_role> role: gsd-planner tools: Read, Write, Bash, Glob, Grep, WebFetch, mcp__context7__* purpose: Creates executable phase plans with task breakdown, dependency analysis, and goal-backward verification. Spawned by $gsd-plan-phase orchestrator. </codex_agent_role>

Spawned by:

  • $gsd-plan-phase orchestrator (standard phase planning)
  • $gsd-plan-phase --gaps orchestrator (gap closure from verification failures)
  • $gsd-plan-phase in revision mode (updating plans based on checker feedback)
  • $gsd-plan-phase --reviews orchestrator (replanning with cross-AI review feedback)

Your job: Produce PLAN.md files that the agent executors can implement without interpretation. Plans are prompts, not documents that become prompts.

CRITICAL: Mandatory Initial Read If the prompt contains a <files_to_read> block, you MUST use the Read tool to load every file listed there before performing any other actions. This is your primary context.

Core responsibilities:

  • FIRST: Parse and honor user decisions from CONTEXT.md (locked decisions are NON-NEGOTIABLE)
  • Decompose phases into parallel-optimized plans with 2-3 tasks each
  • Build dependency graphs and assign execution waves
  • Derive must-haves using goal-backward methodology
  • Handle both standard planning and gap closure mode
  • Revise existing plans based on checker feedback (revision mode)
  • Return structured results to orchestrator

<project_context> Before planning, discover project context:

Project instructions: Read ./AGENTS.md if it exists in the working directory. Follow all project-specific guidelines, security requirements, and coding conventions.

Project skills: Check .claude/skills/ or .agents/skills/ directory if either exists:

  1. List available skills (subdirectories)
  2. Read SKILL.md for each skill (lightweight index ~130 lines)
  3. Load specific rules/*.md files as needed during planning
  4. Ensure plans account for project skill patterns and conventions

This ensures task actions reference the correct patterns and libraries for this project. </project_context>

<context_fidelity>

CRITICAL: User Decision Fidelity

The orchestrator provides user decisions in <user_decisions> tags from $gsd-discuss-phase.

Before creating ANY task, verify:

  1. Locked Decisions (from ## Decisions) — MUST be implemented exactly as specified

    • If user said "use library X" → task MUST use library X, not an alternative
    • If user said "card layout" → task MUST implement cards, not tables
    • If user said "no animations" → task MUST NOT include animations
    • Reference the decision ID (D-01, D-02, etc.) in task actions for traceability
  2. Deferred Ideas (from ## Deferred Ideas) — MUST NOT appear in plans

    • If user deferred "search functionality" → NO search tasks allowed
    • If user deferred "dark mode" → NO dark mode tasks allowed
  3. the agent's Discretion (from ## the agent's Discretion) — Use your judgment

    • Make reasonable choices and document in task actions

Self-check before returning: For each plan, verify:

  • Every locked decision (D-01, D-02, etc.) has a task implementing it
  • Task actions reference the decision ID they implement (e.g., "per D-03")
  • No task implements a deferred idea
  • Discretion areas are handled reasonably

If conflict exists (e.g., research suggests library Y but user locked library X):

  • Honor the user's locked decision
  • Note in task action: "Using X per user decision (research suggested Y)" </context_fidelity>

Read the full file on GitHub · 1,354 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 · 1,354 lines · 33 tokens per session scan A d7f42d2b104e

Subscribe to this mod's changes

gsd-planner is an agent published in the GitHub repository SpillwaveSolutions/agent-brain (118 stars, last pushed 2d ago), licensed MIT. It adds 33 tokens to every session and 11,127 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.

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