feature-review
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.
graduated-implementation
Ramps implementation ambition a notch only after the prior increment is understood. Use when building a feature you must understand, not just ship.
justify
Audits changes for additive bias and Iron Law compliance. Use when reviewing completed work before merging or after AI-assisted implementation.
karpathy-principles
Pre-implementation gate covering think-first, simplicity, surgical edits, and verifiable goals. Use when starting implementation to verify the approach.
latent-space-engineering
Shapes agent behavior via instruction framing and style transfer. Use when composing dispatch prompts or writing skill instructions for parallel review agents.
proof-of-work
Enforces validation and evidence before claiming work complete. Use before declaring implementation done, creating a PR, or submitting deliverables for review.
review-core
Provides review-workflow scaffolding for context, evidence, and output. Use at the start of any detailed review to ensure consistent, comparable findings.
rigorous-reasoning
Applies anti-sycophancy checklist to override agreement bias. Use when analyzing contested claims or avoiding socially convenient but inaccurate conclusions.
scope-guard
Scores feature worthiness and enforces branch-size limits against overengineering. Use when evaluating whether a feature belongs in the current scope or branch.
structured-output
Formats review deliverables with consistent structure for comparable findings. Use when finalizing any review or analysis that must be shared or compared.
vow-enforcement
Classifies and enforces constraints via soft vows, hard vows, and Nen Court layers. Use when designing or auditing enforcement mechanisms for project rules.
workflow-monitor
Detects workflow failures and inefficient patterns then files GitHub issues. Use when a workflow step repeatedly fails or produces inconsistent output.
additive-bias-defense
Inverts burden of proof for code additions. Use when reviewing PRs, planning refactors, or running unbloat to challenge every addition's necessity.
authentication-patterns
Provides auth patterns for API keys, OAuth, and token management. Use when implementing or reviewing service authentication and credential handling.
content-sanitization
Provides sanitization guidelines for external content in skills and hooks. Use when loading GitHub Issues, PRs, WebFetch results, or any untrusted input.
damage-control
Recovers broken agent state via crash recovery, context overflow, and merge conflict protocols. Use when an agent session fails or a worktree is corrupted.
decision-journal
Contract for the project decision journal (tradeoffs and lessons-learned logs). Use when recording a decision, tradeoff, or lesson, or building a consumer hook.
deferred-capture
Defines the contract for deferred-item capture across plugins. Use when building or validating a plugin's deferred-capture wrapper or adding source labels.
document-conversion
Converts documents and URLs to markdown via tiered fallback (MCP markitdown, native tools, user notice). Use when a skill must ingest PDF, DOCX, or URL content.
error-patterns
Provides error classification, recovery, and graceful-degradation patterns. Use when implementing error handling or debugging resilience failures in any skill.
evaluation-framework
Provides weighted scoring, rubrics, and decision-threshold patterns. Use when designing quality gates, evaluation systems, or decision frameworks.
git-platform
Detects git forge (GitHub/GitLab/Bitbucket) and maps CLI commands cross-platform. Use when writing skills that must run on any git hosting provider.
loop-optimization
Decides hand-vs-compiler for loop transforms (unrolling, SIMD, fusion, branchless). Use when reviewing/authoring a hot loop or tempted to hand-optimize one.
markdown-formatting
Enforces markdown line-wrap and structure rules for clean git diffs. Use when writing or editing any committed markdown documentation or skill file.
progressive-loading
Implements hub-and-spoke lazy loading to minimize token usage in large skills. Use when building multi-module skills that need conditional on-demand loading.
pytest-config
Provides standardized pytest config, reusable fixtures, and CI integration patterns. Use when setting up or auditing a Python plugin's test infrastructure.
quota-management
Tracks quotas, monitors thresholds, and degrades gracefully for rate-limited APIs. Use when integrating external services that impose rate or cost limits.
risk-classification
Classifies agent tasks into 4 risk tiers (GREEN/YELLOW/RED/CRITICAL). Use when assessing action reversibility before committing to an approach.
sem-integration
Provides sem semantic-diff detection, install-on-first-use, and fallback patterns. Use when building skills that consume git diff output.
service-registry
Registers external services with health checks, central config, and unified execution. Use when integrating multiple external services needing coordination.
stewardship
Applies stewardship virtues (Care, Curiosity, Humility, Diligence) to plugin work. Use when authoring plugins or reviewing code quality.
storage-templates
Provides templates and lifecycle patterns for storage and documentation systems. Use when organizing knowledge storage, config lifecycle, or naming conventions.
supply-chain-advisory
Audits dependency supply chains for bad versions, lockfile drift, and artifact integrity. Use when adding deps, handling incidents, or releasing a plugin.
testing-quality-standards
Defines testing quality metrics, coverage thresholds, and anti-patterns. Use when establishing test gates or validating a test suite's coverage targets.
usage-logging
Implements structured usage logging and audit trails for cost and session tracking. Use when adding audit trails, usage analytics, or cost tracking to a skill.
utility
Scores agent actions by expected gain, cost, uncertainty, and redundancy. Use when deciding whether to dispatch an agent or invoke a tool.
digital-garden-cultivator
Manages digital garden notes, link structures, and health metrics. Use when curating a knowledge base, pruning stale notes, or tracking content maturity.
knowledge-intake
Processes external resources into stored knowledge with quality scoring and routing. Use when ingesting articles, papers, or docs into a memory palace.
knowledge-locator
Searches and navigates stored knowledge in memory palaces. Use when looking for previously stored information or cross-referencing concepts across palaces.
memory-clarity-probe
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memory-palace-architect
Designs memory palace structures with spatial layouts and domain organization. Use when creating a new palace or planning knowledge architecture by hand.
palace-diagram
Generates Mermaid and ASCII diagrams of palace structure, knowledge topology, and synapse connectivity. Use when inspecting or presenting a palace visually.
palace-index-curator
Curate the web-capture index. Use when the capture backlog grows, captures sit unprocessed at seedling/pending, or to surface stored research during work.
review-chamber
Captures and retrieves PR-review findings in memory palaces. Use after PR review to store architectural decisions, patterns, and standards for future reference.
session-handoff
Decompose a session into typed handoff units and recall them later. Use when ending a session or resuming work whose prior state must be recovered.
session-palace-builder
Builds session-scoped temporary memory palaces for extended conversations. Use when tracking state across interruptions in a multi-step project.
dora-metrics
Computes DORA delivery-performance metrics from git and GitHub API. Use when assessing deployment frequency, lead time, or change failure rate.
github-initiative-pulse
Generates markdown digests and CSV exports for GitHub initiative health. Use when reporting on issue/PR progress across a milestone or project.
release-health-gates
Standardizes release approvals with GitHub-aware checklists and deployment gates. Use before releasing to production to verify all gates pass.
setup
Provisions the oracle ML inference daemon with onnxruntime via uv. Use when setting up local ONNX model inference for skill quality evaluation.
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