fission-ai/openspec

Spec-driven development (SDD) for AI coding assistants.

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Summary Information

Updated 21 minutes ago
Added to GitGenius on August 30th, 2026
Created on August 5th, 2025
Open Issues & Pull Requests: 210 (+0)
GitHub issues: Enabled
Number of forks: 4,607
Total Stargazers: 66,838 (+4)
Total Subscribers: 276 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 46.8 hours
Mean response time: 32.8 days
90th percentile: 149.3 days
Tracked items: 569

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 89% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Work labelled "backlog" is answered fastest, typically in about 16 hours, while "bug" waits about 8 days. 12% of tracked open issues have had no activity in three months. Only 10% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 107
New in 7 days: 10
Closed in 7 days: 7
Avg open age: 118 days
Stale 30+ days: 25
Stale 90+ days: 12

Recent activity

Opened in 7 days: 9
Closed in 7 days: 7
Comments in 7 days: 0
Events in 7 days: 1

Top labels

  • bug (76)
  • design-review (60)
  • enhancement (26)
  • backlog (22)
  • P0-critical (6)
  • future-roadmap (6)
  • integration (6)
  • P2-medium (5)

Detailed Description

OpenSpec is a framework for spec-driven development that enables AI coding assistants to work from detailed specifications.

The tool addresses the challenge of directing AI assistants toward consistent, well-planned code generation by establishing a specification-first workflow. Rather than relying on conversational prompts alone, OpenSpec structures development around formal specifications that define requirements, architecture, and implementation details upfront. This approach provides AI assistants with clear context and constraints, reducing ambiguity and enabling more reliable code generation aligned with intended design.

Teams adopting OpenSpec should consider it when they want to integrate AI coding assistants into a more structured development process. It suits projects where specifications can be written before implementation and where maintaining consistency across AI-generated code matters. The framework is particularly relevant for teams already practicing specification-driven methodologies or those seeking to impose discipline on AI-assisted development workflows.

The project shows active development with regular commits addressing core functionality and user-facing improvements. Work spans both the framework's specification handling capabilities and the developer experience of the tooling. The maintainers are responsive to issues and incorporate feedback into the codebase at a steady pace.