Validate CWICR data quality and estimate inputs. Check for errors, inconsistencies, outliers, and missing data.

Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting.

Analyze and compare subcontractor bids against CWICR benchmarks. Evaluate pricing, identify outliers, and support negotiation.

Break down CWICR work items into component resources. Decompose aggregate items, analyze resource composition, and generate detailed bills of resources.

Assist with quantity takeoff using CWICR data. Calculate quantities from dimensions, apply waste factors, and suggest related work items.

Manage construction change orders from request to approval. Track costs, schedule impacts, and maintain audit trail for dispute prevention.

Optimize crew composition using CWICR labor norms. Balance productivity, cost, and skill requirements for construction crews.

Extract and analyze data from construction ERP systems. Pull project data for analytics, reporting, and integration.

Compare and analyze contractor bids. Score proposals, identify scope gaps, and recommend selections.

Manage construction punch lists for project closeout. Track deficiencies, assign corrections, and monitor completion status.

Automate construction data workflows. Build ETL pipelines and DAG workflows for recurring tasks.

Handles PR review comments and feedback resolution. Use when user wants to resolve PR comments, handle review feedback, fix review comments, address PR review, check review status, respond to reviewer, verify PR readiness, review PR comments, analyze review feedback, evaluate PR comments, assess review suggestions, or triage PR comments. Fetches comments via GitHub CLI, classifies by severity, applies fixes with user confirmation, commits with proper format, replies to threads.

Merges GitHub Pull Requests after validating pre-merge checklist. Use when user wants to merge PR, close PR, finalize PR, complete merge, approve and merge, or execute merge. Runs pre-merge validation (tests, lint, CI, comments), confirms with user, merges with proper format, handles post-merge cleanup.

Search local documents, files, notes, and knowledge bases. Index directories, search with BM25/vector/hybrid, get AI answers with citations. Use when user wants to search files, find documents, query notes, look up information in local folders, index a directory, set up document search, build a knowledge base, needs RAG/semantic search, or wants to start a local web UI for their docs.

Creates GitHub Pull Requests with automated validation and task tracking. Use when user wants to create PR, open pull request, submit for review, or check if ready for PR. Analyzes commits, validates task completion, generates Conventional Commits title and description, suggests labels. NOTE - for merging existing PRs, use github-pr-merge instead.

Creates git commits following Conventional Commits format with type/scope/subject. Use when user wants to commit changes, create commit, save work, or stage and commit. Enforces project-specific conventions from CLAUDE.md.

This skill should be used when the user asks to "integrate DSPy with Haystack", "optimize Haystack prompts using DSPy", "use DSPy to improve Haystack pipeline", mentions "Haystack pipeline optimization", "combining DSPy and Haystack", "extract DSPy prompt for Haystack", or wants to use DSPy's optimization capabilities to automatically improve prompts in existing Haystack pipelines.

This skill should be used when the user asks to "evaluate a DSPy program", "test my DSPy module", "measure performance", "create evaluation metrics", "use answer_exact_match or SemanticF1", mentions "Evaluate class", "comparing programs", "establishing baselines", or needs to systematically test and measure DSPy program quality with custom or built-in metrics.

This skill should be used when the user asks to "create custom DSPy module", "design a DSPy module", "extend dspy.Module", "build reusable DSPy component", mentions "custom module patterns", "module serialization", "stateful modules", "module testing", or needs to design production-quality custom DSPy modules with proper architecture, state management, and testing.

This skill should be used when the user asks to "create a DSPy signature", "define inputs and outputs", "design a signature", "use InputField or OutputField", "add type hints to DSPy", mentions "signature class", "type-safe DSPy", "Pydantic models in DSPy", or needs to define what a DSPy module should do with structured inputs and outputs.