Claude Skills by vamseeachanta

GitHub Actions workflow automation for intelligent CI/CD pipelines with

Gitignore pattern setup and directory scaffolding — covers negation patterns, .gitkeep tracking, and git check-ignore verification workflows

Visual + structural verification of HTML benchmark/validation reports using the Codex-in-Chrome extension. Opens the report in a browser, takes screenshots, checks key DOM elements, and produces a PASS/FAIL verdict. Generic by default; module-specific check lists extend the base set.

A robust workflow for handling a batch of related investigative tasks that require file system research, documentation, and version control.

Break a large umbrella GitHub issue into a layered tree of focused follow-on issues using read-only subagent analysis, then create the issues locally and update docs/parent issue with the issue map.

Guide for building high-quality Model Context Protocol (MCP) servers

Process multiple files in parallel with aggregation and progress tracking.

Diagnose and fix false negatives caused by `grep -q` short-circuiting upstream producers under `set -euo pipefail`.

Code-centric Goal-Oriented Action Planning integrated with SPARC methodology.

Goal-Oriented Action Planning (GOAP) specialist that dynamically creates

Customize or personalize a Codex plugin for a specific organization's tools and workflows by replacing placeholders and configuring MCP servers.

Keep semantic-diff taxonomy summaries consistent with evidence tables when adding richer categories to legacy comparison/reporting pipelines.

Harden Bash automation scripts with TDD-first static and behavioral checks, safe Python invocation via uv, locking, persistent state, and review-driven correction loops.

Shell-based TDD test harness patterns — pass/fail counters, common assertions,

Evaluate all workspace-hub skills for structural validity, content quality,

SPARC Architecture phase specialist for system design, component architecture,

SPARC Pseudocode phase specialist for algorithm design, data structure

SPARC Refinement phase specialist for iterative improvement through TDD,

SPARC Specification phase specialist for requirements analysis, constraint

Execute implementation plans with structured subagent dispatch and two-stage

Verify whether the exact files from a just-completed task are still uncommitted before creating another commit, especially in dirty repos with unrelated churn.

Test-Driven Development methodology enforcing RED-GREEN-REFACTOR cycle. Use for writing tests first, preventing regression, and ensuring code correctness. Based on obra/superpowers.

Safe workflow for fixing bulk test assertion failures in existing test suites — collection errors mask deeper problems, replace_all corrupts, fix source first then tests

Systematically fix failing tests in a test suite — root cause analysis, targeted patches, regression verification, and documentation.

Generate standardized pytest configuration with fixtures, markers, and

Production validation specialist ensuring applications are fully implemented

TDD London School (mockist) specialist for mock-driven, outside-in development.

Optimize development environment, containers, CLI productivity, and git

Six-phase quality gate for code changes. Runs build, typecheck, lint, test, security, and diff-review in sequence. Supports JavaScript/TypeScript, Python, and Rust with auto-detection and skip conditions.

Web application testing toolkit using Playwright with Python. Use for

Generate standardized Python project structure with pyproject.toml, UV

End-to-end workflow for generating reports from data, validating outputs,

Execute configuration-driven analysis workflows from YAML files. Use

Git-track AI agent learnings so they survive machine loss — memory snapshots, corrections, patterns, insights across Codex, Hermes, Codex, and Gemini.

Wire Hermes into workspace-hub ecosystem — multi-repo skills, config sync, session export to learning pipeline, memory cross-pollination, skill patch tracking, and cross-machine health checks.

Class-level Hermes local configuration and setup workflows, including config audit gotchas and Windows installation.

Install and configure a repo-centric Hermes agent workspace on Windows. Covers prerequisites, repo cloning, Python/uv environment, skills system, memory bridge, and multi-agent coordination — the Windows equivalent of the Linux workspace-hub pattern.

Decomposition playbook + specialist-roster conventions + anti-temptation rules for an orchestrator profile routing work through Kanban. The "don't do the work yourself" rule and the basic lifecycle are auto-injected into every kanban worker's system prompt; this skill is the deeper playbook when you're specifically playing the orchestrator role.

Pitfalls, examples, and edge cases for Hermes Kanban workers. The lifecycle itself is auto-injected into every worker's system prompt as KANBAN_GUIDANCE (from agent/prompt_builder.py); this skill is what you load when you want deeper detail on specific scenarios.

Create and manage webhook subscriptions for event-driven agent activation. Use when the user wants external services to trigger agent runs automatically.

Audit Hermes custom config keys and migrated skill settings safely, with verified command behavior and stale-path checks.

Extract structured data from Gmail emails using REST API (no pip dependencies). Covers inbox scanning, subject line regex extraction, email text parsing, thread-aware drafting, and legal-scan-before-commit workflow.

Extract structured data from Gmail inbox emails, enrich with domain-specific

DEPRECATED — superseded by gmail-extract-and-act. Extract emails from Gmail to /mnt/ace/<repo>/, archive to repos, commit, then delete. Uses archive-everything model.

DEPRECATED — superseded by gmail-extract-and-act. Extract Gmail data into archive repo, parse attachments, legal scan, then delete. Uses archive-everything model.

Periodic relationship maintenance via email — identify contacts due for outreach, draft personalized check-ins, queue for user approval. Supports per-account tone and cadence.

Identify and batch-unsubscribe from newsletters and marketing emails across Gmail accounts. Scans List-Unsubscribe headers, generates candidates, executes with user approval.

Normalize, classify, and manage contact databases across 3 Gmail accounts. Clean CSV exports, deduplicate, tag categories, flag touchbase/unsubscribe candidates.

Download attachments from Gmail threads, parse their content (Excel, PDF), extract structured data, and save to target repos with proper legal scanning.

Extract structured data from Gmail emails using REST API (no pip dependencies). Covers inbox scanning, subject line regex extraction, email text parsing, thread-aware drafting, and legal-scan-before-commit workflow.