Crawlora MCP

hermes_suggest

Read-only

Hermes' own search-box autocomplete: matching categories with the number of items behind each, and matching products. The category codes returned are the same pimCodes hermes_category accepts, so a suggestion feeds straight into a category browse. An empty query returns Hermes' default suggestions rather than an error.

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": "hermes_suggest"
  }
}

Input Schema

Name	Required	Description	Default
`query`	No	Partial search term. May be empty, which returns Hermès' default suggestions.
`locale`	No	Market and language, e.g. us_en, fr_fr, jp_ja. Defaults to us_en.

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 5, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the bar is lower. The description adds genuine behavioral context beyond them: the empty-query edge case returns defaults rather than an error, and the returned category codes are the same pimCodes hermes_category accepts, which tells the agent the output is directly reusable.

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 sentences, front-loaded with the core purpose and zero filler. The interoperability detail and edge-case behavior are appended where they belong rather than buried in the opener.

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?

Return values are covered by an output schema, so the description needn't explain them, and annotations carry the safety profile. Params are schema-documented. The description is complete for calling the tool correctly, missing only an explicit routing note versus hermes_search.

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 both query and locale are already documented in the schema. The description restates the empty-query behavior for 'query' but adds no syntax, format, or locale guidance beyond what the schema provides, making the baseline 3 appropriate.

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

Purpose4/5

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

States a specific function – Hermes' search-box autocomplete – and specifies exactly what it returns: matching categories with item counts plus matching products. This distinguishes it from a full hermes_search, though it never names that sibling, so differentiation is implied rather than explicit.

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

Usage Guidelines3/5

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

It notes that a suggestion feeds into a category browse and that an empty query returns defaults, which frames when the tool is useful. However, it never explicitly contrasts this autocomplete against hermes_search or hermes_products, so the agent must infer when to prefer one over the other.

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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