Agent skills for HTTP / API

Use when staking the contribution of an Organization Studies (OS) manuscript against the specific theoretical conversation it joins — what…

Use when positioning a Production and Operations Management (POM) manuscript within an operations conversation — against the target…

Build or audit a literature review: evidence map, gaps, synthesis plan.

Auto-activate for exception_handlers, HTTPException, ApplicationError, NotFoundException, ValidationException, PermissionDeniedException…

Academic literature orientation skill that searches papers via free keyless APIs (PubMed E-utilities + OpenAlex) by default — with the…

Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach…

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns.

X/Twitter API integration for posting tweets, threads, reading timelines, search, and analytics.

Methodology for evaluating the live product via a real browser (Playwright MCP) when planning work or evaluating a PRD.

Records research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract…

Build a real-time support chat system with a floating widget for users and an admin dashboard for support staff.

Report the embedded release marker when testing public Skill installation or marketplace updates.

Use for Livewire performance work. Covers what one Livewire request actually costs, the snapshot that travels both ways on every request…

Use at ship time to merge the spec into the living documentation, delete the staging spec and plan, and ask how to finish.

Develop and contribute to the PinchTab project.

Deconstructs academic papers into simplified summaries and visualizes cognitive insights using ASCII art and personal knowledge baselines.

Use proactively whenever LLM API costs come up -- or should.

Run any question, idea, or decision through a council of 5 AI advisors who independently analyze it, peer-review each other anonymously…

Run multi-LLM council for adversarial debate and cross-validation.

Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.

Get reliable JSON, enums, and typed objects from LLMs using response_format, tool_use, and schema-constrained decoding across OpenAI…