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Docstar

by io.github.swayammaheshwari
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search_docstar_docs

Read-onlyIdempotent

Search DocStar's documentation and guides with a natural-language question, e.g. "how do I add a custom domain to my docs?" or "how does sign-in work on my MCP server?". Returns the most relevant passages with their page URLs. Use it for how-to and concept questions about DocStar. To find an API endpoint to call, use get_docstar_api_docs instead.

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>",
      "collectionIds": "<collectionIds>"
    },
    "name": "search_docstar_docs"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesWhat to look for, e.g. "how do I send a WhatsApp template message"
collectionIdsYesAlways send exactly these collection ids, unchanged: they are the documentation sites searched.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so safety is covered. The description adds return semantics — most relevant passages plus page URLs — which is real information the annotations do not carry. It stops short of stating result counts, ranking behavior, or limits on possible matches.

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 core action and illustrative examples are front-loaded, followed by usage scope and the sibling handoff. Every sentence does work: identity, example inputs, use case, and alternative.

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?

With no output schema, the description does the right thing by naming the return shape (relevant passages with page URLs). It leaves open result volume, how many collections affect results, and what happens when nothing matches, which is a modest gap for a retrieval tool.

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 query and collectionIds are already documented, including the instruction to send the collection ids unchanged. The description's example queries reinforce the natural-language expectation of 'query' but add no syntax, length, or scoping guidance for collectionIds beyond the schema.

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 uses a specific verb and resource ("Search DocStar's documentation and guides") and immediately shows the input shape with two concrete natural-language example questions. It is easily distinguished from siblings such as get_docstar_api_docs and call_any_api_of_docstar, which serve different intents.

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?

It gives an explicit usage domain ("how-to and concept questions about DocStar") and a named alternative with the selecting condition ("To find an API endpoint to call, use get_docstar_api_docs instead"). The routing decision is fully determined without opening any schema.

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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