auto-contextAutomatically read relevant context before major actions. Loads TODO.md, roadmap.md, handoffs, task plans, and other project context files so the AI operates with full situational awareness. Use when starting a task, implementing a feature, refactoring, debugging, planning, or resuming a session.
Install via ClawdBot CLI:
clawdbot install wpank/auto-contextGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://github.com/wpank/ai/tree/main/skills/meta/auto-contextAudited Apr 18, 2026 · audit v1.0
Generated Mar 21, 2026
A development team starts a new sprint by using Auto-Context to load TODO.md and roadmap.md, ensuring all members understand current priorities and milestones before coding. This prevents duplicate work and aligns efforts with project deadlines, especially when integrating with tools like Jira or GitHub.
A marketing agency uses Auto-Context during client handoffs to read handoff notes and task plans, ensuring smooth transitions between teams. This maintains consistency in campaign execution and reduces miscommunication, critical for fast-paced digital marketing projects.
Scientists in a biotech lab activate Auto-Context before planning experiments to load findings.md and CHANGELOG.md, incorporating past discoveries and recent changes. This ensures experiments build on prior results, optimizing resource use and accelerating innovation.
A freelance developer resumes work after a break by using Auto-Context to reload session summaries and TODO.md, quickly rebuilding context without manual file searches. This boosts productivity for solo contractors managing multiple clients with varying project structures.
A startup team implements a new feature by leveraging Auto-Context to read task_plan.md and roadmap.md, ensuring the feature aligns with the product vision and technical constraints. This minimizes rework and helps maintain agile development cycles in resource-limited environments.
Offer Auto-Context as part of a premium AI agent toolkit with monthly subscriptions, targeting development teams and agencies. Revenue comes from tiered pricing based on usage levels and integrations, with upsells for advanced features like custom context file support.
Sell annual enterprise licenses to large corporations for integrating Auto-Context into internal AI workflows, with custom support and security features. Revenue is generated through high-value contracts and ongoing maintenance fees, focusing on industries like finance and healthcare.
Provide a basic version of Auto-Context for free to attract individual developers, then monetize through premium add-ons like staleness alerts and multi-project management. Revenue streams include one-time purchases for advanced modules and microtransactions for extra context slots.
💬 Integration Tip
Integrate Auto-Context with existing project management tools like GitHub or Trello by setting up webhooks to trigger context loading automatically, reducing manual setup and ensuring real-time updates.
Scored Apr 19, 2026
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
Systematic code review patterns covering security, performance, maintainability, correctness, and testing — with severity levels, structured feedback guidance, review process, and anti-patterns to avoid. Use when reviewing PRs, establishing review standards, or improving review quality.
Coding style memory that adapts to your preferences, conventions, and patterns for consistent coding.
Provides a 7-step debugging protocol plus language-specific commands to systematically identify, verify, and fix software bugs across multiple environments.
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
Ship production code with AI agents through acceptance contracts, micro diffs, red green loops, and deterministic handoff checkpoints.