Manage LittlePea pipeline workflow state via SQLite-backed commands.
npx skills add https://github.com/daudaudinang/vibecode --skill lp-state-manager
Please help me install this Agent Skill. Skill: lp-state-manager Source: https://github.com/daudaudinang/vibecode/tree/main/.agents/skills/lp-state-manager Command: npx skills add https://github.com/daudaudinang/vibecode --skill lp-state-manager
Centralizes and standardizes the management of LittlePea pipeline state using a SQLite-backed script, replacing ad-hoc JSON edits and manual grep operations.
Initialize a new workflow for a given plan and begin tracking steps, gates, artifacts, and events with the state manager.
High-intent search queries and answers about installing and using this skill.
You can manage SQLite workflow state by running a Python script that centralizes pipeline tracking, replacing manual JSON edits with structured database commands to create, update, and query workflow steps and artifacts.
Tracking pipeline steps and gates in a SQLite database is done using upsert-step and set-gate commands, which standardize workflow state records and eliminate ad-hoc grep operations across project files.
Yes, you can use Python and SQLite to find existing workflows by plan name using the find-workflows command, which queries the project-scoped database to locate specific pipeline records.
To initialize SQLite workflow state management, run the state manager script inside your repository root, which automatically bootstraps a project-scoped database at .codex/state/pipeline_state.db.
A state manager script derives the next recommended workflow step by evaluating current steps, gates, and artifacts in the SQLite database, using the resolve-next command to calculate the subsequent action.
Yes, the workflow state script requires running inside the repository root directory to correctly locate and bootstrap the project-scoped SQLite database at .codex/state/pipeline_state.db.
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