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Enpitech

by io.github.enpitech
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Search the AI Hub

ai_hub_search
Read-only

Searches the Enpitech AI Hub, Enpitech's curated catalog of Claude Code skills, MCP servers and AI tools, and agentic workflows for frontend teams, each one used by Enpitech engineers in production. Use it when the user wants a skill, MCP server, AI tool or workflow for a frontend task (code review, Figma to code, testing, context files, generative UI and so on), or asks what the AI Hub has. Returns matching items with a one-line take, an overview, the install command when there is one, and a link to the item's page on enpitech.dev. Read-only: it searches a published catalog and sends nothing anywhere.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many results to return, 1-20 (default 8).
queryNoWhat to look for, in plain words: a task, a technology or a name, e.g. "code review", "Figma to React", "MCP servers for React". Omit to list the catalog in order.
categoryNoLimit results to one part of the catalog: skills (Claude Code and Agent Skills), tools (MCP servers and AI tooling) or workflows (agentic workflows and prompts). Omit to search all three.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe search terms, or empty when listing.
totalYesHow many catalog items matched in all.
resultsYesBest matches first.
categoryNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "category": {
+      "enum": [
+        "skills",
+        "tools",
+        "workflows"
+      ],
+      "type": "string"
+    },
+    "query": {
+      "description": "The search terms, or empty when listing.",
+      "type": "string"
+    },
+    "results": {
+      "description": "Best matches first.",
+      "items": {
+        "additionalProperties": false,
+        "properties": {
+          "category": {
+            "enum": [
+              "skills",
+              "tools",
+              "workflows"
+            ],
+            "type": "string"
+          },
+          "install": {
+            "description": "Install command, when the item has one.",
+            "type": "string"
+          },
+          "name": {
+            "type": "string"
+          },
+          "overview": {
+            "type": "string"
+          },
+          "section": {
+            "description": "The catalog section it sits in.",
+            "type": "string"
+          },
+          "summary": {
+            "description": "One-line take from Enpitech.",
+            "type": "string"
+          },
+          "url": {
+            "description": "The item page on enpitech.dev.",
+            "type": "string"
+          }
+        },
+        "required": [
+          "name",
+          "category",
+          "section",
+          "summary",
+          "overview",
+          "url"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "total": {
+      "description": "How many catalog items matched in all.",
+      "type": "number"
+    }
+  },
+  "required": [
+    "query",
+    "total",
+    "results"
+  ],
+  "type": "object"
+}
  2. Added

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already mark readOnlyHint: true, and the description reinforces this with 'Read-only: it searches a published catalog and sends nothing anywhere,' adding a specific privacy/security guarantee beyond the annotation. It also discloses that results include a one-line take, overview, install command, and link, which helps set expectations. Since the safety profile is already annotated, the added context is worthwhile but not extensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is four dense sentences with no fluff: search target, use cases, return contents, and read-only guarantee. Each sentence earns its place, and the most distinguishing information (the catalog search scope) is front-loaded before usage and return details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only search tool with 0 required parameters and an output schema, the description covers the essential context: when to invoke, what it searches, what it returns, and its non-destructive privacy profile. Nothing an agent needs to decide whether to call this tool is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents limit, query, and category with clear descriptions and examples. The tool description adds general usage context (e.g., query examples, 'omit to list the catalog') but does not materially explain the parameters beyond what the schema provides. This aligns with the baseline of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource ('Searches the Enpitech AI Hub') and immediately defines the catalog scope: Claude Code skills, MCP servers, AI tools, and agentic workflows for frontend teams. It uses concrete examples ('code review', 'Figma to code') and is clearly distinct from the unrelated sibling tools like agent_ready and newsletter.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool: 'when the user wants a skill, MCP server, AI tool or workflow for a frontend task... or asks what the AI Hub has.' This gives a clear trigger condition. It does not include an explicit when-not-to-use or alternative tools, but no sibling search tools exist, so the omission is minor.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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