Spec-driven development that adapts to your stack, your team, and your workflow.
SpecOps brings structured spec-driven development to your AI coding assistant — with domain-specific templates for infrastructure, data pipelines, and SDKs, and a built-in team review workflow for shared codebases. Works with Claude Code, Cursor, OpenAI Codex, and GitHub Copilot.
- Domain-specific templates — Infrastructure specs include Rollback Steps and Resource Definitions. Data pipeline specs include Data Contracts and Backfill Strategy. Library specs flag Breaking Changes per task. Backend and fullstack use clean defaults — no unnecessary ceremony.
- Built-in team review cycle — Draft a spec, get section-by-section feedback from teammates, revise, and only implement once
minApprovalsis met. Git identity detection, configurable approval thresholds, and an implementation gate that blocks unapproved specs from proceeding. Solo developers can enableallowSelfApprovalfor a self-review workflow with distinct audit trail. - Security-hardened spec processing — Convention strings and custom templates are sanitized against prompt injection. Secrets use placeholders, PII uses synthetic data, all config fields enforce strict schema validation, and path traversal is rejected at the boundary.
Install (Claude Code):
/plugin marketplace add sanmak/specops
/plugin install specops@specops-marketplace
/reload-plugins
Other platforms & manual install: QUICKSTART.md
Use:
Claude Code: /specops Add user authentication with OAuth | View the spec | List all specs
Cursor / Codex / Copilot: Use specops to add user authentication with OAuth | View the spec | List all specs
Full command reference: docs/COMMANDS.md | Troubleshooting: QUICKSTART.md#troubleshooting
One command triggers a 4-phase workflow: understand your codebase, generate a structured spec, implement it, and verify the result. For vague or high-level ideas, an optional interview mode gathers structured requirements before spec generation.
For vague or exploratory ideas, SpecOps guides you through a structured interview before generating specs. Trigger explicitly with /specops interview I want to build X or say something vague and it auto-triggers. Once approved, SpecOps proceeds to spec generation with enriched context.
For teams, SpecOps adds a structured review cycle between spec creation and implementation. Engineers review specs collaboratively, provide section-by-section feedback, and approve before coding begins. See TEAM_GUIDE.md for the full team workflow.
| Platform | Status | Trigger |
|---|---|---|
| Claude Code | Supported | /specops [description], /specops view, /specops list |
| Cursor | Supported | Use specops to [description], View the ... spec, List all specops specs |
| OpenAI Codex | Supported | Use specops to [description], View the ... spec, List all specops specs |
| GitHub Copilot | Supported | Use specops to [description], View the ... spec, List all specops specs |
| Windsurf | Planned | — |
| Continue.dev | Planned | — |
SpecOps and Spec Kit share the same core philosophy: specs before code. We think Spec Kit is excellent — and we're building on the same principles with a different focus.
Choose Spec Kit if you want the broadest agent support (18+) and are exploring SDD as an individual or small team.
Choose SpecOps if you're a team shipping to production and need specs that match your project type, structured review before implementation, and security-hardened spec processing.
| Capability | SpecOps | GitHub Spec Kit |
|---|---|---|
| Supported platforms | Claude Code, Cursor, OpenAI Codex, GitHub Copilot | 18+ agents |
| Installation | Plugin marketplace or curl | bash, no dependencies |
Python 3.11+ and uv |
| Team review workflow | Built-in (draft → review → revise → approve → gate) | Not available |
| Vertical-aware templates | 7 project types (infra, data, library, builder, etc.) | Generic templates |
| Security hardening | Prompt injection defense, schema validation, path containment | Not documented |
| Platform breadth | 4 platforms | 18+ platforms |
Most AI coding assistants include a plan mode for session-scoped planning. SpecOps adds persistent, reviewable specifications that survive across sessions and team members. Plan mode is a whiteboard sketch; spec mode is the architectural blueprint. Use plan mode for tactical "how" decisions during implementation — use SpecOps when the work spans sessions, involves teammates, or touches code where regressions matter.
Create .specops.json in your project root. Configuration is optional — SpecOps uses sensible defaults.
{
"specsDir": ".specops",
"team": {
"conventions": ["Use TypeScript", "Write tests for business logic"],
"reviewRequired": true,
"specReview": { "enabled": true, "minApprovals": 2 }
},
"implementation": {
"autoCommit": false,
"createPR": true,
"testing": "auto"
}
}See examples/ for minimal, standard, and full configurations. Full schema reference in REFERENCE.md.
SpecOps adapts spec templates to your project type. Set the vertical key in .specops.json or let SpecOps auto-detect from your codebase.
| Vertical | Adaptation |
|---|---|
| Backend | Default templates (API endpoints, services, data models) |
| Frontend | State management, components, UI patterns |
| Full Stack | Handles both frontend and backend layers |
| Infrastructure | Resource definitions, topology, IaC |
| Data Engineering | Pipeline stages, data flow, contracts |
| Library/SDK | Public API surface, developer use cases |
| Builder | Product modules, ship plans, cross-domain tasks |
Full per-vertical documentation and decision trees: REFERENCE.md
Three layers, strict separation:
core/— Platform-agnostic workflow, templates, and safety rules (single source of truth)generator/— Builds platform-specific outputs from core + platform adaptersplatforms/— Generated instruction files per platform (checked into git, no build step for users)
See STRUCTURE.md for the full repository layout.
Contributions welcome. See CONTRIBUTING.md for guidelines.