Buzz Dealer AI

Start a fix

start_fix

The fix for one gap: for ai, a brief with the verified facts and where the text goes (an About sentence, schema JSON-LD, Wikidata statements, a LinkedIn headline, review replies); for you, the steps; for browser, per site the address, the field names and the exact text; for us, the Press Room item and its item id; for specialist, how it works. When the fix was tried before, the answer says when and what happened. Use this when the person picks a gap to work on. Do not use for borderline requests. Side effects: records the attempt in the account's own record; nothing is ordered.

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": {
      "gap_id": "<gap_id>"
    },
    "name": "start_fix"
  }
}

Input Schema

Name	Required	Description	Default
`gap_id`	Yes	The gap id from get_gaps. Example: "5f0c2a9e-7b1d-4c3e-9a8f-2d6b4e1c7a90"

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 18, 2026

changedInput schema / properties / gap_id / description

Previous value: -"The gap_id from get_gaps"New value: +"The gap id from get_gaps. Example: \"5f0c2a9e-7b1d-4c3e-9a8f-2d6b4e1c7a90\""

First observedOct 18, 2026

TDQS

A3.5/5.0

Behavior4/5

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

Annotations only declare readOnlyHint=false, idempotentHint=false, destructiveHint=false, openWorldHint=false. The description adds genuinely useful context beyond that: it discloses side effects ('records the attempt in the account's own record; nothing is ordered') and prior-attempt behavior ('when the fix was tried before, the answer says when and what happened'), which explains the non-idempotent hint in practical terms.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The information is arguably load-bearing (it stands in for a missing output schema), but the delivery is a jargon-dense run-on — 'for ai... for you... for browser... for us... for specialist' — that is not front-loaded with the purpose. The reader must parse the whole sentence before learning what the tool actually does.

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 work of sketching what comes back per consumer, and it covers trigger, exclusion, side effects, and repeat-attempt behavior. It is close to complete for a mutation tool, with only the vague 'borderline requests' exclusion and absent return-shape details holding it back.

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%; the schema itself documents gap_id as a UUID with a format pattern, a sample value, and its provenance ('from get_gaps'). The description adds no parameter-level meaning beyond that, so the baseline of 3 applies.

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

Purpose3/5

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

The name/title anchor it as 'Start a fix,' and the description eventually makes clear it consumes a single gap_id and produces a fix payload. But the opening sentence enumerates output audiences ('for ai... for you... for browser... for us... for specialist') before stating the action cleanly, so the core verb+resource is buried. It also never names a sibling to differentiate from, e.g., plan_fixes or mark_fix_done.

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 gives an explicit trigger ('Use this when the person picks a gap to work on') and an explicit exclusion ('Do not use for borderline requests'). The exclusion is vague — it doesn't route the agent to a specific sibling like check_request — but a when and a when-not are both present, which is above the minimum.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Buzz Dealer AI tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?