Refapp Help

Search Refapp help

search_help

Read-onlyIdempotent

Searches Refapp's help center (support.refapp.com) for articles on how to use Refapp, such as sending reminders to references, project settings or background checks. Returns the best matching articles with title, link, language and a short excerpt. When no article exists in the requested language, articles in other languages are returned.

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": "search_help"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Maximum articles, default 5
`query`	Yes	A few keywords from the question, in the user's language
`language`	No	Language of the question: sv, en, no (Norwegian) or da

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 21, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already cover read-only, idempotent, non-destructive and open-world behavior, so the description only needs to add context — and it does, by disclosing the return fields (title, link, language, excerpt) and the cross-language fallback when no article matches. No rate limits or ranking behavior are mentioned, which is a minor gap at this annotation coverage.

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 purpose and endpoint, then return shape, then the fallback edge case. Every sentence adds information and none repeats the schema.

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?

Even without an output schema, the description states what comes back (title, link, language, excerpt) and how the multi-language case resolves, which is everything an agent needs to call it and interpret results. Topic examples cover the realistic query space.

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 the baseline is 3; the description earns more by adding meaning to the language parameter — articles in other languages are returned when the requested one has no match — and by framing query as user-language keywords. It does not restate the limit cap, but the schema already defines that.

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 verb ("Searches") and resource ("Refapp's help center (support.refapp.com)") and scopes the content with concrete topic examples such as reminders and background checks. It is distinguishable from a fetch-an-article tool, but it never names siblings like get_help_article, so the search-vs-retrieve boundary must be inferred.

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 topical examples ("sending reminders to references, project settings or background checks") make clear what queries belong here, and the language-fallback sentence tells the agent what happens if the requested language has no match. It gives clear usage context but no explicit exclusions or pointers to alternatives for full-article retrieval.

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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