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gsd-2-agent-framework

Meta-prompting, context engineering, and spec-driven development system for autonomous long-running coding agents

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/reason-machines/trending-skills --skill gsd-2-agent-framework
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads gsd-2-agent-framework automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

GSD 2 — Autonomous Spec-Driven Agent Framework

Skill by ara.so — Daily 2026 Skills collection

GSD 2 is a standalone CLI that turns a structured spec into running software autonomously. It controls the agent harness directly — managing fresh context windows per task, git worktree isolation, crash recovery, cost tracking, and stuck detection — rather than relying on LLM self-loops. One command, walk away, come back to a built project with clean git history.


Installation

npm install -g gsd-pi

Requires Node.js 18+. Works with Claude (Anthropic) as the underlying model via the Pi SDK.


Core Concepts

Work Hierarchy

Milestone  →  a shippable version (4–10 slices)
  Slice    →  one demoable vertical capability (1–7 tasks)
    Task   →  one context-window-sized unit of work

Iron rule: A task must fit in one context window. If it can't, split it into two tasks.

Directory Layout

project/
├── .gsd/
│   ├── STATE.md          # current auto-mode position
│   ├── DECISIONS.md      # architecture decisions register
│   ├── LOCK              # crash recovery lock file
│   ├── milestones/
│   │   └── M1/
│   │       ├── slices/
│   │       │   └── S1/
│   │       │       ├── PLAN.md        # task breakdown with must-haves
│   │       │       ├── RESEARCH.md    # codebase/doc scouting output
│   │       │       ├── SUMMARY.md     # completion summary
│   │       │       └── tasks/
│   │       │           └── T1/
│   │       │               ├── PLAN.md
│   │       │               └── SUMMARY.md
│   └── costs/
│       └── ledger.json   # per-unit token/cost tracking
├── ROADMAP.md            # milestone/slice structure
└── PROJECT.md            # project description and goals

Commands

/gsd auto — Primary Autonomous Mode

Run the full automation loop. Reads .gsd/STATE.md, dispatches each unit in a fresh session, handles recovery, and advances through the entire milestone without intervention.

/gsd auto
# or with options:
/gsd auto --budget 5.00        # pause if cost exceeds $5
/gsd auto --milestone M1       # run only milestone 1
/gsd auto --dry-run            # show dispatch plan without executing

/gsd init — Initialize a Project

Scaffold the .gsd/ directory from a ROADMAP.md and optional PROJECT.md.

/gsd init

Creates initial STATE.md, registers milestones and slices from your roadmap, sets up the cost ledger.

/gsd status — Dashboard

Shows current position, per-slice costs, token usage, and what's queued next.

/gsd status

Output example:

Milestone 1: Auth System  [3/5 slices complete]
  ✓ S1: User model + migrations
  ✓ S2: Password auth endpoints
  ✓ S3: JWT session management
  → S4: OAuth integration  [PLANNING]
    S5: Role-based access control

Cost: $1.84 / $5.00 budget
Tokens: 142k input, 38k output

/gsd run — Single Unit Dispatch

Execute one specific unit manually instead of running the full loop.

/gsd run --slice M1/S4            # run research + plan + execute for a slice
/gsd run --task M1/S4/T2          # run a single task
/gsd run --phase research M1/S4   # run just the research phase
/gsd run --phase plan M1/S4       # run just the planning phase

/gsd migrate — Migrate from v1

Import old .planning/ directories from the original Get Shit Done.

/gsd migrate                        # migrate current directory
/gsd migrate ~/projects/old-project # migrate specific path

/gsd costs — Cost Report

Detailed cost breakdown with projections.

/gsd costs
/gsd costs --by-phase
/gsd costs --by-slice
/gsd costs --export costs.csv

Project Setup

1. Write ROADMAP.md

# My Project Roadmap

## Milestone 1: Core API

### S1: Database schema and migrations
Set up Postgres schema for users, posts, and comments.

### S2: REST endpoints
CRUD endpoints for all resources with validation.

### S3: Authentication
JWT-based auth with refresh tokens.

## Milestone 2: Frontend

### S1: React app scaffold
...

2. Write PROJECT.md

# My Project

A REST API for a blogging platform built with Express + TypeScript + Postgres.

## Tech Stack
- Node.js 20, TypeScript 5
- Express 4
- PostgreSQL 15 via pg + kysely
- Jest for tests

## Conventions
- All endpoints return `{ data, error }` envelope
- Database migrations in `db/migrations/`
- Feature modules in `src/features/<name>/`

3. Initialize

/gsd init

4. Run

/gsd auto

The Auto-Mode State Machine

Research → Plan → Execute (per task) → Complete → Reassess → Next Slice

Each phase runs in a fresh session with context pre-inlined into the dispatch prompt:

PhaseWhat the LLM receivesWhat it produces
ResearchPROJECT.md, ROADMAP.md, slice description, codebase indexRESEARCH.md with findings, gotchas, relevant files
PlanResearch output, slice description, must-havesPLAN.md with task breakdown, verification steps
Execute (task N)Task plan, prior task summaries, dependency summaries, DECISIONS.mdWorking code committed to git
CompleteAll task summaries, slice planSUMMARY.md, UAT script, updated ROADMAP.md
ReassessCompleted slice summary, full ROADMAP.mdUpdated roadmap with any corrections

Must-Haves: Mechanically Verifiable Outcomes

Every task plan includes must-haves — explicit, checkable criteria the LLM uses to confirm completion. Write them as shell commands or file existence checks:

## Must-Haves

- [ ] `npm test -- --testPathPattern=auth` passes with 0 failures
- [ ] File `src/features/auth/jwt.ts` exists and exports `signToken`, `verifyToken`
- [ ] `curl -X POST http://localhost:3000/auth/login` returns 200 with `{ data: { token } }`
- [ ] No TypeScript errors: `npx tsc --noEmit` exits 0

The execute phase ends only when the LLM can check off every must-have.


Git Strategy

GSD manages git automatically in auto mode:

main
 └── milestone/M1          ← worktree branch created at start
      ├── commit: [M1/S1/T1] implement user model
      ├── commit: [M1/S1/T2] add migrations
      ├── commit: [M1/S1] slice complete
      ├── commit: [M1/S2/T1] POST /users endpoint
      └── ...
 
 After milestone complete:
main ← squash merge of milestone/M1 as "[M1] Auth system"

Each task commits with a structured message. Each slice commits a summary commit. The milestone squash-merges to main as one clean entry.


Crash Recovery

GSD writes a lock file at .gsd/LOCK when a unit starts and removes it on clean completion. If the process dies:

# Next run detects the lock and auto-recovers:
/gsd auto

# Output:
# ⚠ Lock file found: M1/S3/T2 was interrupted
# Synthesizing recovery briefing from session artifacts...
# Resuming with full context

The recovery briefing is synthesized from every tool call that reached disk — file writes, shell output, partial completions — so the resumed session has context continuity.


Cost Controls

Set a budget ceiling to pause auto mode before overspending:

/gsd auto --budget 10.00

The cost ledger at .gsd/costs/ledger.json:

{
  "units": [
    {
      "id": "M1/S1/research",
      "model": "claude-opus-4",
      "inputTokens": 12400,
      "outputTokens": 3200,
      "costUsd": 0.21,
      "completedAt": "2025-01-15T10:23:44Z"
    }
  ],
  "totalCostUsd": 1.84,
  "budgetUsd": 10.00
}

Decisions Register

.gsd/DECISIONS.md is auto-injected into every task dispatch. Record architectural decisions here and the LLM will respect them across all future sessions:

# Decisions Register

## D1: Use kysely not prisma
**Date:** 2025-01-14
**Reason:** Better TypeScript inference, no code generation step needed.
**Impact:** All DB queries use kysely QueryBuilder syntax.

## D2: JWT in httpOnly cookie, not Authorization header
**Date:** 2025-01-14  
**Reason:** Better XSS protection for the web client.
**Impact:** Auth middleware reads `req.cookies.token`.

Stuck Detection

If the same unit dispatches twice without producing its expected artifact, GSD:

  1. Retries once with a deep diagnostic prompt that includes what was expected vs. what exists on disk
  2. If the second attempt fails, stops auto mode and reports:
✗ Stuck on M1/S3/T1 after 2 attempts
Expected: src/features/auth/jwt.ts (not found)
Last session: .gsd/sessions/M1-S3-T1-attempt2.log
Run `/gsd run --task M1/S3/T1` to retry manually

Skills Integration

GSD supports auto-detecting and installing relevant skills during the research phase. Create SKILLS.md in your project:

# Project Skills

- name: postgres-kysely
- name: express-typescript  
- name: jest-testing

Skills are injected into the research and plan dispatch prompts, giving the LLM curated knowledge about your exact stack without burning context on irrelevant docs.


Timeout Supervision

Three timeout tiers prevent runaway sessions:

TimeoutDefaultBehavior
Soft8 minSends "please wrap up" steering message
Idle3 min no tool callsSends "are you stuck?" recovery prompt
Hard15 minPauses auto mode, preserves all disk state

Configure in .gsd/config.json:

{
  "timeouts": {
    "softMinutes": 8,
    "idleMinutes": 3,
    "hardMinutes": 15
  },
  "defaultModel": "claude-opus-4",
  "researchModel": "claude-sonnet-4"
}

TypeScript Integration (Pi SDK)

GSD is built on the Pi SDK. You can extend it programmatically:

import { GSDProject, AutoRunner } from 'gsd-pi';

const project = await GSDProject.load('/path/to/project');

// Check current state
const state = await project.getState();
console.log(state.currentMilestone, state.currentSlice);

// Run a single slice programmatically
const runner = new AutoRunner(project, {
  budget: 5.00,
  onUnitComplete: (unit, cost) => {
    console.log(`Completed ${unit.id}, cost: $${cost.toFixed(3)}`);
  },
  onStuck: (unit, attempts) => {
    console.error(`Stuck on ${unit.id} after ${attempts} attempts`);
    process.exit(1);
  }
});

await runner.runSlice('M1/S4');

Custom Dispatch Hooks

Inject custom context into any dispatch prompt:

// .gsd/hooks.ts
import type { DispatchHook } from 'gsd-pi';

export const beforeTaskDispatch: DispatchHook = async (ctx) => {
  // Append custom context to every task dispatch
  return {
    ...ctx,
    extraContext: `
## Live API Docs
${await fetchInternalAPIDocs()}
    `
  };
};

Register in .gsd/config.json:

{
  "hooks": "./hooks.ts"
}

Roadmap Reassessment

After each slice completes, GSD runs a reassessment pass that may:

  • Re-order upcoming slices based on discovered dependencies
  • Split a slice that turned out larger than expected
  • Mark a slice as no longer needed
  • Add a new slice for discovered work

The LLM edits ROADMAP.md in place. You can review diffs with:

git diff ROADMAP.md

To disable reassessment:

{
  "reassessment": false
}

Troubleshooting

Auto mode stops immediately with "no pending slices"

All slices in ROADMAP.md are marked [x]. Reset a slice: remove [x] from its entry and delete .gsd/milestones/M1/slices/S3/SUMMARY.md.

LLM keeps failing must-haves

Check .gsd/sessions/ for the last session log. Common causes: must-have references wrong file path, or test command needs environment variable. Adjust must-haves in the task's PLAN.md and re-run with /gsd run --task M1/S3/T2.

Cost ceiling hit unexpectedly

The research phase on large codebases can be expensive. Set researchModel to a cheaper model in config, or reduce codebase index depth.

Lock file left after clean exit

rm .gsd/LOCK
/gsd auto

Git worktree conflicts

git worktree list          # see active worktrees
git worktree remove .gsd/worktrees/M1 --force
/gsd auto                  # recreates cleanly

Session file too large for recovery

If .gsd/sessions/ grows large, GSD compresses sessions older than 24h automatically. Manual cleanup:

/gsd cleanup --sessions --older-than 7d

Links

FAQ

What does the gsd-2-agent-framework skill do?

Meta-prompting, context engineering, and spec-driven development system for autonomous long-running coding agents

How do I install gsd-2-agent-framework?

Run npx skills add https://github.com/reason-machines/trending-skills --skill gsd-2-agent-framework in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/gsd-2-agent-framework/ (personal) or .claude/skills/gsd-2-agent-framework/ (project).

Which AI agents can use gsd-2-agent-framework?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is gsd-2-agent-framework safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains gsd-2-agent-framework?

It is published by reason-machines in reason-machines/trending-skills. It has 1,492 recorded installs.

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