wdm0006

Parses recent Gmail activity and logs interaction summaries to Evergreen CRM contacts — without storing full email bodies. Use when you want to sync email activity to your CRM, update interaction history, or keep Evergreen current with your communications. Requires Gmail connected in Claude.

Parses unstructured text (email signatures, business cards, LinkedIn profiles, meeting notes) into structured Evergreen CRM contacts. Use when adding new contacts from raw text, importing contacts from emails or messages, or batch-creating contacts from event notes.

Researches and enriches Evergreen CRM contacts with publicly available information — LinkedIn details, company info, recent news, and shared context. Use when a contact has sparse details, before an important meeting, or when batch-updating stale records.

Generates a narrative summary of everything known about a contact in Evergreen CRM — how you met, what you've discussed, mutual connections, and pending threads. Use when you need to quickly refresh your memory before reaching out, replying, or meeting someone.

Drafts personalized follow-up emails and messages based on Evergreen CRM contact history, past interactions, and pending actions. Use when you need to write a follow-up email, thank-you note, check-in message, or any outreach to an existing contact.

Batch-processes contacts from a conference, dinner, or networking event into Evergreen CRM — creates records, tags them by event, and drafts personalized follow-up messages. Use after any event where you met multiple new people.

Generates a prioritized follow-up list from Evergreen CRM based on overdue actions, stale contacts, and interaction cadences. Use when planning your week, checking who needs attention, or building a daily outreach list.

Scans Gmail for actionable items and maps them to Evergreen CRM contacts — unanswered questions, promised deliverables, introduction requests, and follow-ups needed. Use when triaging your inbox, catching missed commitments, or syncing email activity to your CRM. Requires Gmail connected in Claude.

Prevents, detects, and remediates files that should never be committed — secrets (.env, API tokens, hardcoded credentials) and dev artifacts (build output, scratch databases, editor/OS files). Covers .gitignore (and why it does not untrack), git rm --cached, auditing tracked files, history scrubbing, and credential rotation. Use when a repo has committed secrets or junk, when setting up a new repo's ignore rules, or when reviewing what a repo actually tracks.

Designs intuitive Python library APIs following principles of simplicity, consistency, and discoverability. Handles API evolution, deprecation, breaking changes, and error handling. Use when designing new library APIs, reviewing existing APIs for improvements, or managing API versioning and deprecations.

Builds command-line interfaces for Python libraries using Click or Typer. Includes command groups, argument handling, progress bars, shell completion, and CLI testing with CliRunner. Use when adding CLI functionality to a library or building standalone command-line tools.

Improves Python library code quality through ruff linting, mypy type checking, Pythonic idioms, and refactoring. Use when reviewing code for quality issues, adding type hints, configuring static analysis tools, or refactoring Python library code.

Builds and manages open source Python library communities including CONTRIBUTING.md, CODE_OF_CONDUCT.md, issue/PR templates, contributor recognition, and GitHub automation. Use when setting up community infrastructure, improving contributor experience, or managing project governance.

Creates comprehensive Python library documentation including Google-style docstrings, Sphinx setup, API references, tutorials, and ReadTheDocs configuration. Use when writing docstrings, setting up Sphinx documentation, or creating user guides for Python libraries.

Comprehensively reviews Python libraries for quality across project structure, packaging, code quality, testing, security, documentation, API design, and CI/CD. Provides actionable feedback and improvement recommendations. Use when evaluating library health, preparing for major releases, or auditing dependencies.

Packages and distributes Python libraries using modern pyproject.toml, build backends (setuptools, hatchling), PyPI publishing with trusted publishing, and wheel building. Use when packaging libraries for distribution, publishing to PyPI, or troubleshooting packaging issues.