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Moltline Studio

by com.moltlinestudio
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Search Catalog

search_catalog
Read-onlyIdempotent

Search all 138 catalog products by keyword and/or focus area. FREE.

Typical input {"query": "email inbox", "limit": 5} returns a ranked list of product objects [{"slug": ..., "name": ..., "area": ..., "segment": ..., "tagline": ...}]. An empty query with an area set browses that area.

Use when the caller names a keyword, product, or focus area to look up. Not for bundles (list_kits) and not for plain-language problem statements, which recommend_products ranks by fit rather than keyword match. Errors: on invalid, missing, or malformed input this tool never raises a protocol error; it returns {"error": ""}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_catalog"
  }
}

Input Schema

NameRequiredDescriptionDefault
areaNoOptional focus-area filter; one of "productivity", "developertools", "personalassistant", "creative", "industryspecific", "educational". Empty means all areas.
limitNoMaximum results to return; values outside 1-100 are clamped. Default 15.
queryNoSpace-separated keywords matched against name, tagline, slug, and segment, e.g. "email inbox".

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), yet the description adds the error contract — no protocol errors on bad input, instead an {"error": ...} payload — and the retry guarantee after correction. That is real behavioral context an agent cannot get from the annotations.

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

Conciseness4/5

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

Purpose is front-loaded, the example is compact, and the routing sentence follows immediately. Slight redundancy in enumerating the returned object fields, which the output schema already covers, and the error sentence is a touch long.

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 3-optional-param read-only search with full schema coverage, output schema, and complete annotations, nothing an agent needs is missing: trigger, exclusions, browse mode, error handling, and return shape are all covered.

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

Parameters4/5

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

Schema coverage is 100%, so all three parameters are already documented; the description still adds cross-parameter semantics the schema lacks, notably that an empty query with an area set switches the tool into browse mode. The rendered product-object example further clarifies which fields matter.

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?

States a specific verb and resource ("Search all 138 catalog products") plus the exact match fields (keyword and/or focus area), and explicitly rules out bundles and problem-statement lookups. An agent can distinguish it from list_kits and recommend_products without opening any schema.

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

Usage Guidelines5/5

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

Gives a positive trigger ("Use when the caller names a keyword, product, or focus area") and two explicit exclusions naming the correct alternatives: list_kits for bundles and recommend_products for plain-language problem statements. It also documents the browse-mode variant (empty query + area).

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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