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Crawlora MCP

Crawlora MCP

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by Crawlora-org
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JavaScript
Remote

goat_suggest

Autocomplete partial GOAT search queries to return matching curated collections and products, and discover collection slugs for collection and search endpoints.

Instructions

Autocomplete a GOAT search. Returns GOAT's own search-box autocomplete for a partial query: matching curated collections and matching products. The collections carry the slug values accepted by GET /goat/collection and by GET /goat/search's collection_slug parameter, making this the way to discover collection slugs.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "goat_suggest"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum curated collections to return. Defaults to 8, maximum 20. Does not affect the product count, which upstream fixes at 25
queryYesPartial search text to autocomplete

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.16.2

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden, and it does disclose that output mirrors GOAT's own search-box autocomplete (i.e., curated, bounded suggestions) and that collections double as usable slug identifiers. It does not state the read-only/non-destructive profile, pagination, or that product results are capped upstream (that fact sits only in the schema).

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?

Three tight sentences, front-loaded with the core action, then the return contents, then the practical payoff (slug discovery). No filler and nothing redundant with structured fields.

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

Completeness4/5

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

For a simple 2-parameter autocomplete tool with no output schema and no annotations, the description covers what it returns and why it matters, which is sufficient. Minor gaps remain around safety profile and result-count behavior, but the essential calling context is present.

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 limit and query parameters are already fully documented in the schema, including the 8-default/20-max and fixed 25-product behavior. The description adds no additional parameter-level syntax or format detail, so the baseline 3 applies.

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 ('Autocomplete a GOAT search') and enumerates the two return categories: curated collections and products. It explicitly names the sibling endpoints the returned slugs feed into (GET /goat/collection, GET /goat/search), so an agent can distinguish it from goat_search or goat_collection without opening a schema.

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?

Clearly frames the tool as the slug-discovery path ('making this the way to discover collection slugs'), which tells the agent when to prefer it over a full search. It stops short of stating an explicit exclusion (e.g., 'do not use for full product results, use goat_search instead'), so it is strong context without a named counter-case.

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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