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.
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.
[](https://agentmods.dev/agents/spillwavesolutions/agent-brain/gsd-planner)<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>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.
| Model | Per session | Once 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 |
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 Copies of this mod
6 near-identical copies found in the catalogue:
- gsd-planner — 95% identical, 97 lines differ
- thrunt-hunt-planner — 95% identical, 143 lines differ
- gsd-planner — 95% identical, 144 lines differ
- gsd-planner — 95% identical, 717 lines differ
- gsd-planner — 92% identical, 188 lines differ
- gsd-planner — 86% identical, 295 lines differ
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:
$gsd-plan-phaseorchestrator (standard phase planning)$gsd-plan-phase --gapsorchestrator (gap closure from verification failures)$gsd-plan-phasein revision mode (updating plans based on checker feedback)$gsd-plan-phase --reviewsorchestrator (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:
- List available skills (subdirectories)
- Read
SKILL.mdfor each skill (lightweight index ~130 lines) - Load specific
rules/*.mdfiles as needed during planning - 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:
-
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
-
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
-
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>
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.
- today First seen · 1,354 lines · 33 tokens per session scan A d7f42d2b104e
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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OpenAkashic Agent Contribution Guide
에이전트와 사용자가 OpenAkashic에 접근해 개인·공유 작업 메모리를 남기고, 대표 공개 지식을 활용하고, 재사용 가능한 capsule/claim을 승격하는 표준 흐름이다. MCP를 쓰는 에이전트도, skills 문서와 API 토큰만 쓰는 에이전트도 같은 정책을 따른다.
OpenAkashic Skills Guide
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agent
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