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Atomic Traceability for AI-Driven Development — a governance framework that constrains AI coding agents via gated, atomic, context-pinned phases.

Project description

Atomic Spec

Stop your AI from vibe-coding.

PyPI Python License Agents supported Status

Spec-kit taught AI agents a workflow. Atomic Spec makes them obey it. When /atomicspec.implement runs, the agent is architecturally prevented from reading plan.md or spec.md — it sees only the current task file, pre-loaded with every registry value, domain rule, and gate criterion it needs. No drifting mid-feature. No hallucinating a new approach on pass three. No 800-line "kitchen sink" PRs.

uv tool install atomic-spec
atomicspec init my-project --ai claude

TL;DR — One AI instruction file isn't enough. Atomic Spec enforces eight non-negotiable rules: one task per file, AI sees only the current task during coding, human sign-off at four checkpoints, and a project registry that remembers every decision. If you've ever reviewed an AI PR and thought "where did this pattern come from?" — that's the problem this exists to kill.


Status

v0.1.x · first public release. The core governance model (Eight Prime Directives, Context Pinning, Atomic Injunction) is stable and exercised on every release. APIs and command names may evolve through v0.x. Claude Code is the reference implementation and validated end-to-end; 12 other agents are experimental (templates install correctly, agent-specific wiring not yet exhaustively tested). See the agent tier table below.


Why not just use [X]?

Atomic Spec occupies a specific slot in the AI-coding ecosystem. Here's where it fits:

Tool Enforcement Context isolation Cross-feature consistency Audit trail
AGENTS.md / .cursorrules / CLAUDE.md Soft guidance in a single file None Relies on the agent re-reading None
aider conventions file Soft guidance, per-session None Manual Git history only
continue.dev rules Soft guidance, IDE-integrated None Manual None
github/spec-kit (upstream) Workflow templates; agent is asked nicely None (agent reads everything) Templates, not enforced None
Atomic Spec Gated phases + forbidden-reads during implementation Context Pinning: agent sees only current task file Project Defaults Registry enforced on every command Registry changelog + per-task traceability matrix

If you want recommendations for your AI, the tools above are lighter and fine. If you want the AI to physically not be able to drift — because it cannot see the thing that would let it drift — that's what Atomic Spec adds.


The Eight Prime Directives

Article IX of memory/constitution.md hardcodes eight non-negotiable rules. Every command in the framework enforces them.

# Directive Rule
1 Directory Supremacy Every feature MUST have an index.md (dashboard) and traceability.md (matrix)
2 Atomic Injunction /atomicspec.tasks is FORBIDDEN from creating a single tasks.md — must create tasks/ directory with individual T-XXX-[name].md files
3 Context Pinning During /atomicspec.implement, AI is FORBIDDEN from reading plan.md — may ONLY read index.md, the specific task file, and traceability.md
4 Gate Compliance MUST follow Knowledge Station gate criteria before phase transitions
5 Knowledge Routing When encountering unknown decisions, MUST consult Station Map first, then the specific station
6 Human-In-The-Loop During /atomicspec.plan, AI MUST pause at 4 checkpoints for user approval
7 Project Defaults Registry All commands MUST read specs/_defaults/registry.yaml and enforce project-wide standards
8 Self-Contained Tasks Task files MUST embed all context (registry, domain rules, gate criteria) for implementation

The Assembly Line Mental Model

Atomic Spec treats AI-driven development like a factory assembly line, not a freeform workshop. Every phase of your work is a station, and the product (your code) moves from one station to the next only when it passes inspection.

  • Stations — each phase (specify → plan → tasks → implement) is a discrete station with a clear job. Knowledge Stations in .specify/knowledge/stations/ extend this: 18 procedural guides covering every aspect of building a SaaS product.
  • Deliverables — each station outputs tangible artifacts: a spec file, a plan document, atomic task files, production code. If you can't open it, read it, run it, or test it, it's not a deliverable.
  • Gates — each station ends with objective pass/fail criteria. "Feels good" is never a gate. The spec has edge cases or it doesn't. The tenancy model is decided or it isn't.
  • Core ruleno gate pass → no proceeding. You cannot enter planning without a passing spec. You cannot generate tasks without a passing plan. You cannot implement without passing gates.

This is the entire reason Atomic Spec exists: AI coding agents produce drift when they operate without gates. The assembly line replaces vibes with checkpoints.


Before and After

Before — a single tasks.md After — atomic tasks/T-XXX-*.md (enforced)
# Tasks for 003-user-auth

- [ ] Set up JWT library
- [ ] Create /login endpoint
- [ ] Add password hashing
- [ ] Add rate limiting
- [ ] Write tests
- [ ] Add forgot-password flow
... 34 more ...

Problem: AI reads the whole file on every implementation run. Context window fills with sibling tasks. No embedded decisions, so the agent re-derives the tech stack each pass — often differently. No way to trace which task satisfies which requirement.

specs/003-user-auth/
├── index.md            # feature dashboard
├── traceability.md     # FR → task matrix
└── tasks/
    ├── T-001-scaffold-jwt-config.md
    ├── T-002-implement-login-endpoint.md
    ├── T-003-password-hashing.md
    └── ...

Each task file embeds: registry values it must obey, domain rules from the relevant subagent, a verification command, and which requirement (FR-012) it satisfies. During /atomicspec.implement, the agent is forbidden from reading anything else.


Quick Start

Install

# Preferred: install the CLI as an isolated tool
uv tool install atomic-spec

# Alternative: pipx
pipx install atomic-spec

Initialize a project

atomicspec init my-project --ai claude     # or --ai cursor-agent, copilot, gemini, windsurf
cd my-project
git checkout -b 001-your-feature-name

Use the slash commands in your AI agent

/atomicspec.constitution              # establish project principles (once)
/atomicspec.specify "your feature"    # generate a spec with gate criteria
/atomicspec.plan                      # produces plan.md, pauses at 4 HITL checkpoints
/atomicspec.tasks                     # writes tasks/T-XXX-*.md (never a single tasks.md)
/atomicspec.implement                 # Context-Pinned implementation, one task at a time

See docs/quickstart.md for the full walkthrough, including optional commands (/atomicspec.clarify, /atomicspec.analyze, /atomicspec.checklist, /atomicspec.cleanup, /atomicspec.analyze-competitors, /atomicspec.taskstoissues) and the init-project.{sh,ps1} script path for offline/local installs.

AI coding agents supported

Supported tier (validated end-to-end): Claude Code · Cursor · GitHub Copilot · Gemini CLI · Windsurf

Experimental tier (templates install correctly, agent-specific wiring not exhaustively tested): Qwen Code · opencode · Codex CLI · Kilo Code · Auggie CLI · CodeBuddy · Qoder CLI · Roo Code · Amazon Q Developer CLI · Amp · SHAI · IBM Bob

Experimental-tier issues are labeled experimental and triaged best-effort. PRs that promote an agent to Supported tier are welcome — see SUPPORT.md for triage policy and promotion criteria.


Project Defaults Registry

Constitution Directive 7 introduces a central source of truth for project-wide technical decisions.

What It Does

The Project Defaults Registry at specs/_defaults/registry.yaml stores all project-wide technical decisions:

# specs/_defaults/registry.yaml
version: 2
architecture:
  pattern: monolith          # or microservices, serverless
  layers: clean              # or mvc, vertical_slice
  api_style: rest            # or graphql, grpc
code_patterns:
  data_access: repository    # or active_record, query_builder
  error_handling: result_type # or exceptions, error_codes
  validation_approach: schema # or manual, decorator
backend:
  language: typescript
  framework: express
database:
  type: postgresql
  tenancy_model: shared_db_tenant_id
# ... 80+ configurable decisions

How It Works

Phase Action
On Entry Every command reads registry, applies existing defaults
During Work New decisions prompt user: "Add to project defaults?"
On Exit Registry sync checkpoint collects all new decisions with HITL approval
Deviation Using a different value requires explicit DEVIATION block + approval

HITL Requirements

Every registry change requires Human-In-The-Loop approval:

══════════════════════════════════════════════════════════════
📋 REGISTRY SYNC - Phase 0.9 Checkpoint
══════════════════════════════════════════════════════════════

The following decisions were made in this planning session
and are NOT yet in the project defaults registry:

| Key                      | Value           | Add to Registry? |
|--------------------------|-----------------|------------------|
| backend.language         | typescript      | Candidate        |
| backend.framework        | express         | Candidate        |

Adding these to the registry means ALL future features
will use these as defaults.
══════════════════════════════════════════════════════════════

Audit Trail

All changes are logged in specs/_defaults/changelog.md:

### 2026-02-06 | backend.language
- **Changed**: `null``typescript`
- **Why**: Decided during user-auth feature planning
- **Source**: specs/001-user-auth/plan.md
- **Approved by**: Human (accept)

Self-Contained Tasks (Knowledge Wiring)

Constitution Directive 8 ensures task files contain ALL context needed for implementation.

The Problem

During /atomicspec.implement, Context Pinning (Directive 3) prevents reading:

  • plan.md, spec.md
  • .specify/knowledge/stations/*
  • .specify/subagents/*
  • Other task files

This meant subagents were "blind" to project patterns and had to guess.

The Solution

During /atomicspec.tasks, ALL context is embedded INTO each task file:

# T-025-create-user-repository

## 📋 Embedded Context (READ THIS FIRST)

### Project Standards (from registry)
| Key | Value |
|-----|-------|
| `architecture.layers` | clean |
| `code_patterns.data_access` | repository |
| `database.tenancy_model` | shared_db_tenant_id |

### Domain Rules (from data-architecture subagent)
- **Tenancy**: Every query MUST filter by `tenant_id`
- **No naked queries**: All DB access through repository methods only
- **Audit columns**: Include `created_at`, `updated_at`, `created_by`

### Gate Criteria (from data-architecture subagent)
- [ ] Repository interface defined with tenant-scoped methods
- [ ] No direct ORM calls outside repository
- [ ] All queries filter by tenant_id

---

## 🎯 Objective
Create the UserRepository class implementing the repository pattern...

Graceful Degradation

Not all projects have all knowledge sources:

Missing Source Action
Registry Embed: "No registry - using plan.md decisions"
Subagent Check for full station file, extract key rules
Station Embed: "No domain knowledge available"
Everything Embed plan.md decisions directly, note limited context

Tasks are NEVER blocked by missing knowledge sources.


Dynamic Agent Discovery

21 specialized subagents are available in .specify/subagents/, matched dynamically based on feature needs.

How It Works

Agent selection is NOT hard-coded. Instead:

  1. Scan available agents: Read all *.md files in .specify/subagents/ (excluding _* files)
  2. Extract metadata: Parse YAML frontmatter for name and description
  3. Match by keyword overlap: Compare spec/task keywords against each agent's YAML description
  4. Load relevant agents: Only agents whose description matches the feature's needs

Example Matching

Spec mentions "REST API", "endpoints"
  → Agent description: "Design RESTful APIs, microservice boundaries..."
  → Match: backend-architect ✓

Spec mentions "payment", "subscription"
  → Agent description: "Integrate Stripe, PayPal, and payment processors..."
  → Match: payment-integration ✓

Available Subagents

Agent Domain
backend-architect REST APIs, microservices, database schemas
data-architecture Database design, tenancy models, migrations
frontend-developer React components, responsive layouts, state management
payment-integration Stripe, PayPal, checkout flows, subscriptions
database-optimizer SQL optimization, indexes, query performance
deployment-engineer CI/CD, Docker, Kubernetes, infrastructure
code-reviewer Code quality, security, maintainability
typescript-pro Advanced TypeScript, generics, strict typing
python-pro Idiomatic Python, decorators, async/await
sql-pro Complex SQL, CTEs, window functions
ui-ux-designer Interface design, wireframes, accessibility
performance-engineer Profiling, bottlenecks, caching strategies
prompt-engineer LLM prompts, AI features, agent orchestration

The full roster lives at .specify/subagents/ — 21 base agents (ai/, backend/, business/, data/, design/, devops/, frontend/, languages/, review/, security/, testing/) plus 146 mobile-specific agents under mobile/ organized by lifecycle phase. Each agent is a markdown file with YAML frontmatter that /atomicspec.tasks and /atomicspec.implement read for routing.

Adding Custom Agents

Create .specify/subagents/custom/your-agent.md:

---
name: your-agent
description: Your agent's purpose and keywords for matching
model: opus  # or sonnet, haiku
---

Agent instructions here...

The agent will be automatically discovered and matched when features mention keywords from its description.


Atomic Traceability Workflow

Phase Flow

/atomicspec.specify  -->  /atomicspec.AnalyzeCompetitors (optional)  -->  /atomicspec.plan  -->  /atomicspec.tasks  -->  /atomicspec.implement
     |                           |                                       |                    |                     |
     v                           v                                       v                    v                     v
  spec.md                  competitive-analysis/                   Phase 0.0: Registry    tasks/               Execute with
  + Gates 03-05            summary.md + competitors/               Phase 0.1: Domain      T-XXX-*.md           Context Pinning
  + Registry check         🛑 User review                          Phase 0: Research      index.md             + Registry
                           (accept/revise/reject)                  Phase 0.5: HITL #1     traceability.md      as reference
                                                                   Phase 0.6: Validate    + Embedded Context
                                                                   Phase 0.7: HITL #2     (from registry,
                                                                   Phase 0.8: HITL #3     subagents, gates)
                                                                   Phase 0.9: HITL #4
                                                                   Phase 1: Design
                                                                   + Gates 06-13

Planning Phases Explained

Phase Name Purpose
0.0 Load Registry Read project defaults, pre-populate tech decisions
0.1 Load Domain Knowledge Dynamically discover and load relevant subagents/stations
0 Research Resolve unknowns, research best practices
0.5 HITL #1: Tech Stack User approves language, framework, database choices
0.6 Validation Check package compatibility, deprecation, conflicts
0.7 HITL #2: Validation Review User reviews warnings, approves overrides
0.8 HITL #3: UI Specs User selects UI library, state management, design system
0.9 HITL #4: Registry Sync User approves adding new decisions to project defaults
1 Design Generate data models, API contracts, architecture

Competitive Analysis (Optional)

The /atomicspec.AnalyzeCompetitors command is optional but recommended for customer-facing products. It follows Station 03 (Discovery) procedures:

  1. User Research Check - Asks if you have existing competitive research to share
  2. Search Frame - Defines primary, adjacent, and substitute categories
  3. Competitor Benchmarking - Analyzes 5-15 competitors on positioning, pricing, workflows, integrations, and weak points
  4. Pain Mining - Extracts user complaints from reviews, forums, and support docs
  5. Synthesis - Produces wedge candidates and recommends a differentiation strategy

Output Structure:

specs/[feature]/competitive-analysis/
├── summary.md              # Main reference for downstream commands
├── user-research/          # Your existing research (if provided)
└── competitors/
    ├── competitor-1.md
    ├── competitor-2.md
    └── ...

HITL Review: After analysis, you review the summary and can:

  • Accept - Keep for use in /atomicspec.plan
  • Revise - Request changes
  • Reject - Delete entirely (downstream commands proceed without competitive context)

Why "Reject" Deletes Everything: If you don't want competitive analysis influencing decisions, the folder is deleted. This signals to /atomicspec.plan that no competitive context exists, so it makes decisions based on general knowledge only. This is intentional - no analysis means no competitive influence.

Human-In-The-Loop Checkpoint (Phase 0.5)

During /atomicspec.plan, after Phase 0 (Research) completes, the AI MUST PAUSE and present all tech stack decisions for user approval:

══════════════════════════════════════════════════════════════
🛑 TECH STACK REVIEW - Phase 0.5 Checkpoint
══════════════════════════════════════════════════════════════

| Decision          | Value             | Source   |
|-------------------|-------------------|----------|
| Language/Version  | Python 3.11       | Spec     |
| Storage           | PostgreSQL        | Assumed  |

⚠️ ASSUMPTIONS: Storage was assumed based on SaaS patterns.

Reply "proceed", "revise: [changes]", or ask questions.
══════════════════════════════════════════════════════════════

Why this matters: Tech stack decisions are expensive to change post-implementation. This checkpoint prevents AI from making assumptions that lead to rework.

Gate Checkpoints

Each phase requires passing specific Knowledge Station gates:

Phase Command Required Gates
Specification /atomicspec.specify Station 03 (Discovery), 04 (PRD), 05 (User Flows)
Planning /atomicspec.plan Station 06 (API), 07 (Data), 08 (Auth), 12 (CI/CD), 13 (Security)
Task Generation /atomicspec.tasks Validates all prior gates, creates atomic structure
Implementation /atomicspec.implement Context Pinning enforced - reads only current task

Context Pinning (Implementation Phase)

During /atomicspec.implement, the AI operates under strict constraints:

ALLOWED to read:

  • index.md - Feature dashboard (entry point)
  • Current T-XXX-*.md task file only
  • traceability.md - For marking completion

FORBIDDEN from reading:

  • plan.md - Contains too much context, causes drift
  • Other task files - One task at a time
  • spec.md - Already distilled into tasks

This prevents "kitchen sink" implementations and ensures focused, atomic execution.


Knowledge Stations

Atomic Spec includes 18 Knowledge Stations in .specify/knowledge/stations/:

# Station Purpose Gate Phase
01 Introduction Manual overview, Assembly Line concept Foundation
02 Roles & Ownership RACI matrix, Gate responsibilities Foundation
03 Discovery ICP, Wedge, JTBD, Competitors Specify
04 PRD Spec MVP scope, SaaS rules, Acceptance criteria Specify
05 User Flows Edge states, RBAC, Information Architecture Specify
06 API Contracts OpenAPI, error schema, Idempotency Plan
07 Data Architecture Tenancy model, isolation, ADRs Plan
08 Auth & RBAC Session/JWT, permissions, Security hardening Plan
09 Billing Stripe integration, Webhooks, State machine Plan
10 Metering & Limits Usage tracking, Quotas, Cost control Plan
11 Observability Logging, tracing, Alerting, Runbooks Plan
12 CI/CD & Release Environments, pipelines, Migrations Plan
13 Security Threat model, baseline, AppSec workflow Plan
14 Data Lifecycle Retention, GDPR, Backups, Deletion Plan
15 Performance Latency targets, Caching, Load testing Scale
16 Analytics Event tracking, Funnels, Dashboards Scale
17 Admin Tooling Support panel, Playbooks, Audit logging Scale
18 Documentation PRD/ADR templates, Repo structure Scale

Feature Directory Structure

After running the full workflow, your project looks like:

your-project/
│
│   PROJECT-WIDE DEFAULTS (/atomicspec.plan creates, all commands use):
│
├── specs/_defaults/
│   ├── registry.yaml    # Source of truth for project-wide tech decisions
│   ├── changelog.md     # Audit trail (what/when/why/who)
│   └── README.md        # Registry documentation
│
│   FEATURE-SPECIFIC FILES:
│
├── specs/001-feature-name/
│   ├── spec.md              # Feature specification (/atomicspec.specify)
│   │
│   │   COMPETITIVE ANALYSIS (optional, /atomicspec.AnalyzeCompetitors):
│   │
│   ├── competitive-analysis/
│   │   ├── summary.md       # Main reference doc (patterns, pains, wedge)
│   │   ├── user-research/   # User's custom materials (if provided)
│   │   └── competitors/     # Individual competitor analyses
│   │       ├── competitor-1.md
│   │       └── ...
│   │
│   │   IMPLEMENTATION PLANNING (/atomicspec.plan):
│   │
│   ├── plan.md              # Implementation plan
│   ├── research.md          # Technical research
│   ├── data-model.md        # Database schema
│   ├── quickstart.md        # Dev setup guide
│   ├── contracts/           # API contracts (OpenAPI)
│   │
│   │   ATOMIC TRACEABILITY STRUCTURE (/atomicspec.tasks):
│   │
│   ├── index.md             # Feature dashboard - THE entry point
│   ├── traceability.md      # Requirement-to-task mapping matrix
│   └── tasks/               # Atomic task directory (NOT tasks.md!)
│       ├── T-001-setup-project.md     # Each task has Embedded Context:
│       ├── T-010-create-user-model.md # - Project Standards (from registry)
│       ├── T-020-implement-endpoint.md# - Domain Rules (from subagents)
│       ├── T-021-add-validation.md    # - Gate Criteria (from stations)
│       └── ...
│
│   SUBAGENTS (21 specialized agents, dynamically discovered):
│
└── .specify/subagents/
    ├── backend-architect.md
    ├── data-architecture.md
    ├── frontend-developer.md
    └── ... (18 more)

Task File Naming Convention

Tasks follow a numbering scheme by phase:

Range Phase
T-001 to T-009 Setup & Configuration
T-010 to T-019 Foundation (models, core)
T-020 to T-036 User Story 1 - Features
T-037 to T-039 User Story 1 - Wiring (routes, nav, stores)
T-040 to T-056 User Story 2 - Features
T-057 to T-059 User Story 2 - Wiring
T-060 to T-076 User Story 3 - Features
T-077 to T-079 User Story 3 - Wiring
T-080 to T-089 Cross-cutting concerns
T-090 to T-099 Final verification

⚠️ Wiring Tasks are MANDATORY - Every user story must include wiring tasks that:

  • Register backend routes in the main app file
  • Add frontend routes to the app router
  • Add navigation links to sidebar/nav components
  • Connect frontend stores/hooks to backend endpoints

Available Commands

Core Workflow Commands

Command Description
/atomicspec.specify Create feature specification with Knowledge Station gates
/atomicspec.AnalyzeCompetitors Optional - Analyze competitors following Station 03 discovery procedures
/atomicspec.plan Create implementation plan with architecture gates
/atomicspec.tasks Generate atomic task files (index.md, traceability.md, tasks/)
/atomicspec.implement Execute tasks with Context Pinning
/atomicspec.cleanup Detect and remove orphaned code, unused components, dead routes

Supporting Commands

Command Description
/atomicspec.constitution View/update project constitution
/atomicspec.clarify Clarify underspecified requirements
/atomicspec.analyze Cross-artifact consistency analysis
/atomicspec.checklist Generate quality validation checklists
/atomicspec.taskstoissues Convert tasks to GitHub issues

Cleanup Command Details

The /atomicspec.cleanup command helps maintain a clean codebase by detecting:

  • Frontend: Orphan components, dead routes, unused stores
  • Backend: Unregistered routes, unused services, dead endpoints
  • Database: Orphan tables, unused columns, stale migrations

Key Features:

  • Tech-stack adaptive - Detects your stack (React, FastAPI, etc.) and offers appropriate tools
  • Per-domain control - Choose detection method for each domain independently
  • External tools optional - Use tools like knip (JS/TS) or vulture (Python), or AI-based detection
  • Feature history aware - AI-based detection uses previous SpecKit features to boost confidence (e.g., "file created in 001, spec says 003 replaces it")
  • Report first, delete later - Never auto-deletes; generates report, asks for approval
  • Database schema audit - Compares schema against codebase to find unused tables/columns

Workflow:

  1. Detect project structure (frontend/backend/database)
  2. For each domain: ask user to choose detection method (tool / AI / skip)
  3. Run detection and categorize findings (SAFE / REVIEW / KEEP)
  4. Generate cleanup-report.md with findings
  5. User reviews and approves deletions
  6. Execute cleanup with test verification

Two-Tier Governance System

Atomic Spec implements a two-tier governance hierarchy:

Tier 1: Constitution (memory/constitution.md)

  • Immutable project principles
  • Article IX: Prime Directives (Atomic Traceability)
  • Cannot be overridden by any phase

Tier 2: Assembly Line Manual (.specify/knowledge/)

  • Knowledge Stations with gate criteria
  • Templates that enforce gates
  • Scripts that validate compliance

Prior art

Atomic Spec forks github/spec-kit by Den Delimarsky and John Lam, adding the Atomic Traceability Model on top. The original Spec Kit introduced Spec-Driven Development as a practice; this fork makes it enforced rather than encouraged.

For upstream docs on Spec-Driven Development itself, see the spec-kit repository. For the deep-dive on Atomic Traceability specifically, see atomic-traceability-model.md.


Troubleshooting

PowerShell Execution Policy (Windows)

If the init script doesn't run, use:

powershell -ExecutionPolicy Bypass -File ".\init-project.ps1" -TargetPath "D:\MyProject" -AIAgent "claude"

Git Credential Manager on Linux

If you're having issues with Git authentication on Linux, you can install Git Credential Manager:

#!/usr/bin/env bash
set -e
echo "Downloading Git Credential Manager v2.6.1..."
wget https://github.com/git-ecosystem/git-credential-manager/releases/download/v2.6.1/gcm-linux_amd64.2.6.1.deb
echo "Installing Git Credential Manager..."
sudo dpkg -i gcm-linux_amd64.2.6.1.deb
echo "Configuring Git to use GCM..."
git config --global credential.helper manager
echo "Cleaning up..."
rm gcm-linux_amd64.2.6.1.deb

Commands Not Available in Claude Code

If /atomicspec.* commands don't appear:

  1. Ensure .claude/commands/ directory exists in your project
  2. Verify command files are named atomicspec.*.md (e.g., atomicspec.specify.md)
  3. Restart Claude Code after adding commands

License

This project is licensed under the terms of the MIT open source license. Please refer to the LICENSE file for the full terms.


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Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

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