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THE AGENSI STORE
172 skills found
by Shandra
Finds accessibility problems in UI code and turns them into prioritized fixes, WCAG-aware checklists, test plans, remediation tickets, and safe AI coding prompts.
Automated security auditing and risk assessment for Model Context Protocol (MCP) servers.
by Shandra
Transforms undocumented repositories into professional README files, setup guides, command maps, architecture notes, environment references, testing docs, and AI agent handoff files.
by Julian
A rigorous security auditor that scans code for OWASP Top 10 vulnerabilities with severity ratings and concrete fixes.
by Matthew King
Audit, score, and improve your AI agent skills for higher quality, lower token costs, better reliability, and marketplace success. Get actionable recommendations for prompts, instructions, tool usage, error handling, and user experience.
by LocoLoboZ
Orchestrate independent reviews, adversarial audits, and multimodal analysis via secondary models and external tools.
by Shandra
Professional DevOps diagnostics for AI agents to solve failed deployments, Docker crashes, and CI/CD pipeline errors.
by LocoLoboZ
A proactive governance layer that validates MCP tool intent and scope to ensure safe, compliant agent behavior.
Audit your frontend build against a performance budget and catch size regressions before you ship. Flags total bundle over budget, initial bundle over budget, individual chunks over a threshold, oversized image assets, source maps shipped to production, and large unminified JavaScript. Reads a webpack or Vite-style stats.json plus a perf-budget.json you control.
Lint the function-calling tool definitions your agent exposes. Flags tools with no description, parameters missing a description or a type, overlapping or near-duplicate tools, too many tools for reliable selection, an unsafe tool exposed without a guard, required parameters missing from the schema, and free-form parameters that should be bounded with an enum. Cleaner tool schemas mean an agent that picks the right tool.
Scaffold and audit secure MCP servers with input schemas, confirmation gates, and safety-first tool definitions.
Generate a shareable stat card for any repo, with an honest health grade. It reads the file tree and renders a card showing the language mix, file count and size, whether tests, docs, and a license are present, and an A-to-F health grade from a documented rubric. Markdown by default, SVG with a flag. The kind of card people actually post.
Transform fragile AI prototypes into resilient, enterprise-ready production agents with professional hardening tools.
An adversarial gate to verify AI-use disclosures and draft compliant provenance statements for any venue.
by Corey Jacobs
Generate source-safe repository audits and repair handoff bundles without mutating your code.
Turns Claude into a senior WordPress launch reviewer that audits a site, theme, or plugin against the entire pre-launch standard across 7 weighted domains and returns one objective go/no-go decision with a scored blocker list.
A senior WordPress theme architect skill that migrates classic PHP themes to FSE block themes — extracting business logic into a companion plugin during conversion — and delivers both a phased reversible plan and the actual converted files.
Scaffold a secure, spec-compliant MCP server from a description of the tools you want to expose. Sets up the official SDK (TypeScript or Python/FastMCP), defines tools/resources/prompts with strict JSON Schema, wires the right transport (stdio or Streamable HTTP), adds OAuth 2.1 for remote, and hardens against the MCP-specific footguns — prompt injection via tool output, token passthrough, over-broad scopes, command/path/SSRF injection, leaked secrets — before it ships. Returns a runnable skeleton plus a security checklist. Built by someone who's shipped production MCP servers.
by Corey Jacobs
Run a buyer-readiness check before publishing an AI agent skill package.
A professional technical editor's review for your docs. Catches missing context, unclear writing, and unverifiable claims in READMEs, API docs, and changelogs before they ship — with a PASS/REVISE verdict and a prioritized fix list.
Write and review the docs AI agents actually read — AGENTS.md for your repo and llms.txt for your site. Drafts them from scratch or audits existing ones for completeness, clarity, and wasted context, with a PASS or REVISE verdict.
Design and write the eval suite for your LLM-powered feature — the metrics that match your failure modes, a golden dataset plan with starter cases, anchored rubrics, LLM-as-judge prompts with the known bias mitigations, and pass/fail gates wired for CI.
Generate consistent API reference docs from your code, OpenAPI spec, or route handlers — per-endpoint parameters, real request and response examples, error codes, auth, and copy-pasteable curl, written for the developer calling the API.
Generate a complete, reader-ready README from your code and project details — not a template dump. It leads with what the project is and why, gives a quickstart that actually runs, and includes only the sections that apply.