imbue

Makes agent reasoning visible, surfaces tradeoffs, and fades help so humans build judgment. Use when reviewing or learning from agent-written code.

Summarizes recent git changes for context recovery after session breaks. Use when resuming work after a gap or handing off to another session.

Verifies a package exists before install, defending against hallucination and slopsquatting. Use when adding, recommending, or installing a package.

Analyzes changesets with risk scoring, categorization by type and impact, and release note preparation. Use when extracting insights from raw change data.

Scores backlog items with RICE/WSJF/Kano and files GitHub issues for top candidates. Use when triaging a roadmap or prioritizing features for a sprint.

Ramps implementation ambition a notch only after the prior increment is understood. Use when building a feature you must understand, not just ship.

Audits changes for additive bias and Iron Law compliance. Use when reviewing completed work before merging or after AI-assisted implementation.

Pre-implementation gate covering think-first, simplicity, surgical edits, and verifiable goals. Use when starting implementation to verify the approach.

Shapes agent behavior via instruction framing and style transfer. Use when composing dispatch prompts or writing skill instructions for parallel review agents.

Enforces validation and evidence before claiming work complete. Use before declaring implementation done, creating a PR, or submitting deliverables for review.

Provides review-workflow scaffolding for context, evidence, and output. Use at the start of any detailed review to ensure consistent, comparable findings.

Applies anti-sycophancy checklist to override agreement bias. Use when analyzing contested claims or avoiding socially convenient but inaccurate conclusions.

Scores feature worthiness and enforces branch-size limits against overengineering. Use when evaluating whether a feature belongs in the current scope or branch.

Formats review deliverables with consistent structure for comparable findings. Use when finalizing any review or analysis that must be shared or compared.

Classifies and enforces constraints via soft vows, hard vows, and Nen Court layers. Use when designing or auditing enforcement mechanisms for project rules.

Detects workflow failures and inefficient patterns then files GitHub issues. Use when a workflow step repeatedly fails or produces inconsistent output.