GitHub
testing-skills-with-subagents
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
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Development AI Skills
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GitHub
executing-plans
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...
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GitHub
exec
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...
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GitHub
memory-coordination
Coordinates Serena MCP knowledge graph operations for Shannon Framework. Enforces standardized entity naming (shannon/* namespace), relation creation patterns, search protocols, and observation management. Prev...
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GitHub
skill-discovery
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...
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GitHub
performance-regression-detection
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...
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GitHub
verification-before-completion
Use when about to claim work is complete, fixed, passing, or successful, before committing or creating PRs - requires running verification commands and confirming output before making ANY success claims; eviden...
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GitHub
shannon-analysis
FLEXIBLE skill orchestrating comprehensive analysis workflows. Adapts to analysis type (codebase, architecture, technical debt, complexity) and automatically invokes appropriate sub-skills (spec-analysis, proje...
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GitHub
finishing-a-development-branch
Use at development completion - guides branch integration with Shannon 3-tier validation (0.00-1.00 readiness score), MCP merge pattern analysis, and Serena risk assessment
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GitHub
mcp-discovery
Intelligent MCP server recommendation engine based on quantitative domain analysis. Maps project domains (Frontend %, Backend %, Database %, etc.) to appropriate MCP servers using tier-based priority system (Ma...
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GitHub
root-cause-tracing
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack with quantitative tracking, adding instrumentation when n...
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GitHub
context-restoration
Restore previous session state from Serena MCP checkpoints. Retrieves checkpoint by ID or auto-selects most recent, deserializes context, restores command/skill/phase/wave state. Use when: resuming after contex...
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GitHub
spec-analysis
8-dimensional quantitative complexity analysis with domain detection. Analyzes specifications across structural, cognitive, coordination, temporal, technical, scale, uncertainty, dependency dimensions producing...
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GitHub
testing-claude-plugins-with-python-sdk
Use when testing Claude Code plugins programmatically, building SDK applications, encountering plugin loading failures (plugins array empty), getting AttributeError on message.type, or needing verified Claude A...
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GitHub
confidence-check
5-check quantitative validation ensuring 90% confidence before implementation. Prevents wrong-direction work through systematic verification: duplicate check (25%), architecture compliance (25%), official docs...
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GitHub
forced-reading-auto-activation
Use automatically when prompts exceed 3000 characters, files exceed 500 lines, or large files are referenced - enforces complete line-by-line reading protocol with quantitative comprehension verification before...
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GitHub
shannon-execution-verifier
Comprehensive post-build verification of Shannon Framework's application outputs using three-layer methodology: Flow Verification (execution trace analysis), Artifact Verification (physical output inspection),...
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GitHub
functional-testing
Enforce NO MOCKS testing philosophy with real systems. Iron Law: no mock objects, no unit tests, no stubs. Test with real browsers (Puppeteer MCP), real databases, real APIs. Enforced via post_tool_use.py hook....
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GitHub
using-shannon
Use at session start - establishes Shannon Framework workflows including mandatory 8D analysis before implementation, NO MOCKS testing enforcement, wave-based execution for complexity >=0.50, and automatic Sere...
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GitHub
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation with quantitative tracking, pattern analysis, hypothesis testing, imp...
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GitHub
test-driven-development
Use when implementing any feature or bugfix, before writing implementation code - write the test first using REAL systems (NO MOCKS), watch it fail, write minimal code to pass; ensures tests actually verify beh...
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GitHub
wave-orchestration
True parallel sub-agent coordination with wave-based execution. Analyzes phase dependencies, groups independent phases into waves for parallel execution, allocates agents based on complexity score. Proven 3.5x...
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GitHub
task-automation
Orchestrates Shannon's complete workflow: prime → spec → wave. Automates session preparation, specification analysis, and wave execution in one command. Interactive by default with validation gates, --auto for...
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GitHub
architecture-evolution-tracking
Track architectural decisions and detect drift from ADRs (Architecture Decision Records). Calculate alignment score (0.00-1.00) showing code-to-design conformance. Auto-detect architectural violations and sugge...
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