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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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glNous
hlNoen
depthNo
freshNo
queryYes
locationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds non-obvious behavioral context: results are constrained to organic positions 1-100 and filtered to forum/community domains, which tells the agent what kind of result set it will get. It omits rate limits, result count, and how the filtering is applied, keeping it below a 5.

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?

Two sentences, front-loaded with the mechanism (search + filter) before the use cases, with no filler. The second sentence drifts slightly into soft marketing framing ('customer problem discovery') rather than adding operational detail.

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

Completeness3/5

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

With no output schema and six undocumented parameters, the description explains the tool's purpose but not enough for an agent to configure a call correctly (locale, depth, freshness behavior). It is adequate for understanding what comes back but incomplete for parameterized 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 0% across six parameters (gl, hl, depth, fresh, query, location), so the description carries the full burden. It only loosely gestures at position range, which may relate to 'depth', and says nothing about gl/hl locale codes or location. The parameter gap is largely unaddressed.

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+resource ('Search Google and filter organic results ... for community discussions and forum threads') and enumerates the target sources (Reddit, Quora, HackerNews, StackExchange, niche forums). This is clearly differentiated from siblings like google_serp or ai_answers without opening either schema.

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 explicit use cases ('ideal for sentiment analysis, user discussions, and customer problem discovery'), which is clear context for when to reach for this tool. It does not, however, name an alternative tool or state when not to use it (e.g., vs. plain google_serp or ai_answers), so it falls short of full routing guidance.

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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