Vera

Forum and Discussion Finder

find_discussion_candidates

Read-only

Search Google and filter organic results (positions 1-100) specifically for community discussions and forum threads (Reddit, Quora, HackerNews, StackExchange, niche forums). Ideal for sentiment analysis, user discussions, and customer problem discovery. The most the call can cost is held first and you are charged for what it returns; a call that fails costs nothing.

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": "find_discussion_candidates"
  }
}

Input Schema

Name	Required	Description	Default
`gl`	No		us
`hl`	No		en
`depth`	No
`fresh`	No
`query`	Yes
`location`	No
`idempotency_key`	No	Optional. Send the same key (16 to 128 letters, digits, _ . : -) to retry this exact call safely: a retry within 24 hours returns the first result and is not charged again.

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 21, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations only cover readOnlyHint and openWorldHint, and the description goes beyond them with useful billing semantics: a cost ceiling is held first, you pay only for what is returned, and failed calls are free. It also discloses the result-position window (1-100). It does not describe the return shape or result ordering, but with no output schema that is a modest gap.

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?

Three sentences, purpose front-loaded, then use cases, then cost behavior. Every sentence carries information and none is filler, though the billing sentence could be tightened slightly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter tool with 14% schema coverage and no output schema, the description leaves the agent guessing on depth, fresh, gl/hl, and location, all of which materially change results. It covers purpose and cost well but is not complete enough for confident invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 14% (effectively just idempotency_key), and the description explains none of the six remaining parameters. Cryptic names like gl, hl, depth, and fresh get no meaning, syntax, or default rationale from the prose; only 'positions 1-100' faintly hints at the depth cap.

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?

States a concrete verb and resource ('Search Google and filter organic results ... specifically for community discussions and forum threads') plus the scope (positions 1-100) and named sources (Reddit, Quora, HackerNews, StackExchange). This cleanly separates it from generic sibling tools like google_serp and search.

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?

Gives clear usage contexts ('sentiment analysis, user discussions, and customer problem discovery'), which tells the agent when this tool is the right pick over a plain SERP call. It stops short of naming alternatives explicitly or stating when not to use it, so it lands at 4 rather than 5.

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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