Automate the OpenSpec lifecycle from GitHub issues to code artifacts.
npx skills add https://github.com/fjpulidop/specrails-core --skill sr-implement
Please help me install this Agent Skill. Skill: sr-implement Source: https://github.com/fjpulidop/specrails-core/tree/main/templates/skills/sr-implement Command: npx skills add https://github.com/fjpulidop/specrails-core --skill sr-implement
sr-implement orchestrates a complete OpenSpec lifecycle using specialized AI agents (architect, developer, reviewer, and doc-sync) to transform GitHub issues or feature descriptions into ready-to-ship specifications and code artifacts.
Install and run the sr-implement pipeline to process a backlog item or issue, providing either an issue number or a natural-language feature description to begin.
High-intent search queries and answers about installing and using this skill.
You can automate feature implementation from GitHub issues by running a deterministic OpenSpec pipeline that assigns specialized AI agents to architecture, development, review, and documentation phases. It transforms issue descriptions into ready-to-ship code and specifications.
The OpenSpec lifecycle is a deterministic workflow that uses AI agents to design, implement, test, and document features. It enforces mandatory phases like architecture, development, review, and doc-sync to ensure traceability and auditability from issue to deployment.
Yes, AI agents can process multi-issue backlogs by coordinating the architect, developer, reviewer, and doc-sync phases across multiple issues. The pipeline handles multi-feature merges and conflict detection within its deterministic workflow.
Yes, you need git and compatible AI agents to run the OpenSpec pipeline. The deterministic workflow orchestrates these agents through mandatory architecture, implementation, testing, and documentation phases to generate code artifacts from your features.
The pipeline handles reviewer feedback and code conflicts through a deterministic workflow that includes conflict detection and reviewer phases. AI agents coordinate to resolve issues during the implementation and validation stages before finalizing documentation.
Yes, the AI agent feature implementation pipeline supports an optional dry-run mode. This allows you to test the deterministic OpenSpec workflow and validate the architect, developer, and reviewer phases before applying actual code changes.
yareliCamachoConvert feature tasks into dependency-ordered GitHub issues.
jankneumannMerge approved pull requests and archive OpenSpec proposals to finalize features.
marcusagmAutomate full-stack app scaffolding from natural language requests into executable plans.
fjpulidopCoordinate specialized AI agents through deterministic OpenSpec lifecycle phases.
