JanuaryLabs
- 10 skills
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- 1 day ago last updated
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- ▌ Agent Testing · januarylabs bundleTest code built on AI SDK v7 using its real `ai/test` utilities and V4 provider protocol. Use when writing, fixing, reviewing, or migrating tests around AI SDK agents, generation, streaming, structured output, tools, provider registries, model modalities, or simulated streams. Trigger for requests to test an agent, mock a model, fake a stream, simulate a tool call, test retry logic, inspect prompts, or debug hanging streams and empty output. Remove V3 fixtures and custom helpers that duplicate public AI SDK APIs.
- ▌ Text2sql System Prompt Updater · januarylabsUpdate the Text2SQL system prompt in a generalizable, non-overfit way using failure-pattern driven evaluation loops. Use when SQL generation quality regresses or specific failure classes repeat.
- ▌ Feature Development · januarylabsBuild a repository feature by discovering the current flow, resolving ambiguity, implementing the smallest fitting design, and reviewing the diff.
- ▌ Reuse · januarylabsAnalyze a target piece of code and propose how to make it reusable across the rest of the codebase. Walks through phases — understand → survey → design → migration plan — and only edits code after the user approves the plan. Codebase-agnostic. Run only when the user explicitly invokes it (e.g. `/reuse`, "make this reusable", "extract this", "find duplicates of this").
- ▌ Commit · januarylabs bundleWrite conventional commit messages with type, scope, and subject when the user wants to commit changes or save work.
- ▌ Write Docs · januarylabs bundleGenerate documentation for a package by analyzing source code. Use when the user wants to write, create, or generate new documentation pages for a package from scratch.
- ▌ Update Docs · januarylabs bundleUpdate documentation based on code changes since last push. Use when the user wants to update, sync, or refresh documentation to match recent code changes across packages.
- ▌ Doc Gardener · januarylabs bundleKeep repository documentation accurate and agent-legible through drift detection and deterministic fixes. Use when asked to scan docs for stale content, broken links, metadata/nav drift, API coverage gaps, or to run recurring documentation gardening in on-demand or scheduled maintenance loops.