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Data & AI AI Skills

Discover Data & AI skills, compare source repositories and read the instructions for each workflow.

Categories: Data & AI

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GitHub

goal-alignment

krzemienski

QUANTITATIVE skill for validating wave deliverables against goal milestones using 0-100% alignment scoring. Prevents scope drift, detects misalignment, enforces goal-wave consistency. Requires goal-management f...

GitHub

context-preservation

krzemienski

PROTOCOL skill for checkpoint-based context preservation using Serena MCP. Automatically creates checkpoints at wave boundaries and before PreCompact. Enables zero-context-loss multi-session work with structure...

GitHub

writing-plans

krzemienski

Use when design is complete and you need detailed implementation tasks for engineers with zero codebase context - creates comprehensive implementation plans with Shannon quantitative analysis, exact file paths,...

GitHub

brainstorming

krzemienski

Use when creating or developing ideas before writing code or implementation plans - refines rough ideas into fully-formed designs through collaborative questioning with Shannon quantitative validation, alternat...

GitHub

subagent-driven-development

krzemienski

Use for implementation plans - dispatches fresh subagent per task with quality scoring (0.00-1.00), code review gates, Serena pattern learning, and MCP tracking

GitHub

forced-reading-protocol

krzemienski

Use when analyzing critical documents, specifications, or large files (>3000 lines), before any synthesis or conclusions - enforces complete line-by-line reading with quantitative verification to prevent skimmi...

GitHub

intelligent-do

krzemienski

Context-aware task execution with Serena MCP backend. First time: Explores project, saves to Serena, runs spec if complex, executes waves. Returning: Loads from Serena (

GitHub

defense-in-depth

krzemienski

Use when invalid data causes failures deep in execution, requiring validation at multiple system layers - validates at every layer data passes through using Shannon validation gates to make bugs structurally im...

GitHub

honest-reflections

krzemienski

Systematic gap analysis for claimed vs actual work completion. Uses 100+ sequential thoughts to identify assumptions, partial completions, missing components, and rationalization patterns. Validates completion...

GitHub

security-pattern-detection

krzemienski

Detect OWASP Top 10 vulnerabilities via static analysis. Calculate security score (0.00-1.00) for code quality. Auto-generate remediation suggestions with implementation examples. Integrate with Serena for vuln...

GitHub

testing-anti-patterns

krzemienski

Use when writing or changing tests, adding mocks, or tempted to add test-only methods to production code - prevents testing mock behavior, production pollution with test-only methods, and mocking without unders...

GitHub

phase-planning

krzemienski

Generate 5-phase implementation plan with validation gates and resource allocation. Adapts phase count and timeline based on complexity score. Includes validation gates between phases. Use when: planning implem...

GitHub

sitrep-reporting

krzemienski

Military-style SITuation REPort protocol for multi-agent coordination. Enforces structured status reporting with 🟢🟡🔴 codes, quantitative progress (0-100%), blockers, dependencies, ETAs, and authorization cod...

GitHub

project-indexing

krzemienski

Generates SHANNON_INDEX for 94% token reduction (58K → 3K tokens). Compresses large codebases into structured summaries with Quick Stats, Tech Stack, Core Modules, Dependencies, Recent Changes, and Key Patterns...

GitHub

dispatching-parallel-agents

krzemienski

Use for 3+ independent failures - dispatches parallel subagents with Shannon wave coordination, success scoring (0.00-1.00) per domain, and MCP result aggregation

GitHub

condition-based-waiting

krzemienski

Use when tests have race conditions, timing dependencies, or inconsistent pass/fail behavior - replaces arbitrary timeouts with condition polling to wait for actual state changes, eliminating flaky tests with q...

GitHub

writing-skills

krzemienski

Use when creating new skills, editing existing skills, or verifying skills work before deployment - applies TDD to process documentation with Shannon quantitative validation by testing with subagents before wri...

GitHub

mutation-testing

krzemienski

Verify test quality by injecting mutations into code and measuring catch rate. Calculate mutation score (0.00-1.00) showing test effectiveness. Auto-generate missing tests to improve coverage. Integrate with Se...

GitHub

testing-skills-with-subagents

krzemienski

Use before skill deployment to verify pressure resistance via TDD RED-GREEN-REFACTOR cycle with Serena metrics tracking - measures compliance score (0.00-1.00) across pressure scenarios

GitHub

executing-plans

krzemienski

Use when partner provides a complete implementation plan to execute in controlled batches with review checkpoints - loads plan, reviews critically with Shannon quantitative analysis, executes tasks in complexit...

GitHub

exec

krzemienski

Autonomous task execution with library discovery, 3-tier validation, and atomic git commits. Integrates with Shannon CLI Python modules for platform-specific execution. Invokes /shannon:wave for code generation...

GitHub

memory-coordination

krzemienski

Coordinates Serena MCP knowledge graph operations for Shannon Framework. Enforces standardized entity naming (shannon/* namespace), relation creation patterns, search protocols, and observation management. Prev...

GitHub

skill-discovery

krzemienski

Use when needing to discover available skills across project/user directories - automatically scans for SKILL.md files, parses YAML frontmatter, extracts metadata (name, description, type, MCP requirements), an...

GitHub

performance-regression-detection

krzemienski

Track performance benchmarks and detect regressions exceeding 10% threshold. Analyze historical trends and alert on degradation. Calculate regression score (0.00-1.00) for performance health. Integrate with Ser...

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.

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