Docstar

send_feedback_to_docstar

Destructive

Sends feedback straight to the DocStar team. Use it when the user wants to report a bug, request a feature, flag wrong or missing docs, or share praise about DocStar or this MCP server. Write the message in the user's words and add any useful context, such as the tool or endpoint involved and what went wrong. Who sent it (user and organization) is taken from the signed-in user's token, never from the body. Returns 200 once delivered; 400 for an invalid body; 502 if it couldn't be delivered, in which case tell the user and try again later. Authenticate with the proxy_auth_token header (an Authorization: Bearer hm_... DocStar API token or a DocStar JWT is also accepted). Body fields: message (string, required) - The feedback, 1 to 5000 characters.type (string, optional) - One of bug, feature_request, docs, praise, other; default other.collectionId (string, optional) - The collection the feedback is about, if any.context (object, optional) - Extra details, e.g. the tool or endpoint used, the request and the error. POST https://api.docstar.io/feedback/ai

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": "send_feedback_to_docstar"
  }
}

Input Schema

Name	Required	Description
`type`	No	e.g. bug
`context`	No	e.g. {"tool":"get_docstar_mcp_api_docs"}
`message`	No	e.g. get_api_docs didn't list the MCP Server module's new endpoints
`collectionId`	No	e.g. RoNWaspA9p3Z

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 27, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations only give generic hints (destructive=true, not idempotent), while the description adds substantial context the agent could not otherwise know: sender identity comes from the signed-in token and is never read from the body, the full status-code contract (200/400/502), and retry guidance on 502. Auth requirements (proxy_auth_token header or Bearer hm_.../JWT) are spelled out, which is exactly what annotations cannot convey.

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?

The core purpose and usage conditions are front-loaded and the response semantics follow immediately, so an agent gets what it needs in the first two sentences. It is long and the 'Body fields' block largely restates the schema, but that section is set off at the end rather than cluttering the opening.

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 one-shot write tool with no output schema, the description covers everything needed: what to send, how to compose it, where identity comes from, auth options, and how to interpret 200/400/502 including a retry instruction. Nothing material is left for the agent to guess.

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, but the description genuinely adds meaning: the message length bound (1–5000), the actual allowed values for `type` (bug, feature_request, docs, praise, other) where the schema only says 'e.g. bug', and a concrete example of what belongs in `context`. That enum listing is value the schema does not provide.

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 first sentence names a specific verb and destination ('Sends feedback straight to the DocStar team'), and the following clause enumerates the exact purposes (bug, feature request, docs gap, praise). No sibling tool overlaps this function, and the agent can identify it immediately.

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?

It clearly states the trigger conditions ('when the user wants to report a bug, request a feature, flag wrong or missing docs, or share praise') and even gives composition advice ('write the message in the user's words'). There is no explicit when-not or comparison to a sibling, but the tool is functionally unique so the gap is minor.

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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