Batch processor
Process multiple documents in bulk with parallel execution
Skills for your AI
Process multiple documents in bulk with parallel execution
Chain document operations into reusable pipelines
Access 1200+ AI Agent tools via Model Context Protocol (MCP)
Automate document workflows with n8n - 7800+ workflow templates
MCP server with 39 tools for Word, Excel, PowerPoint, PDF, OCR operations
Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
Use when you need to address review or issue comments on an open GitHub Pull Request using the gh CLI.
Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
Use when asked to ship a SaaS MVP, audit application security, build an AI agent, run browser QA, or design a domain model with multiple skills and verified checkpoints.
Clarify requirements before implementing. Use when serious doubts arise.
Companion to atlas-contract. Auto-invoked by its Final Audit on caught drift; also use after Post Reviews or user requests to record a mistake. Distills drift into WHEN/DON'T/INSTEAD clauses, writes to Atlas.md after confirmation.
Automate Bitbucket repositories, pull requests, branches, issues, and workspace management via Rube MCP (Composio). Always search tools first for current schemas.
Use before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.
description: Feature development pipeline - research, plan, track, and implement major features.
Automate changelog generation from commits, PRs, and releases following Keep a Changelog format. Use when setting up release workflows, generating release notes, or standardizing commit conventions.
Use when a coding task must be completed against explicit acceptance criteria with minimal user re-intervention across implementation, review feedback, deployment, and runtime verification.
ALWAYS use this skill when committing code changes — never commit directly without it. Creates commits following Sentry conventions with proper conventional commit format and issue references. Trigger on any commit, git commit, save changes, or commit message
Execute tasks from a track's implementation plan following TDD workflow
Manage track lifecycle: archive, restore, delete, rename, and cleanup
Create a new track with specification and phased implementation plan
Git-aware undo by logical work unit (track, phase, or task)
Configure a Rails project to work with Conductor (parallel coding agents)
Display project status, active tracks, and next actions