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by ai.howseen
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Get easiest wins

get_easiest_wins
Read-only

Third-party sites and pages cited in the answers the brand loses (competitor named, brand not), ranked by how many lost answers cite them, with the matching action-plan item. Getting listed there is the shortest path back into those answers.

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": "get_easiest_wins"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoEnd date YYYY-MM-DD. Default: now.
fromNoStart date YYYY-MM-DD. Default: all time.
langNoLanguage of the action texts (default en).
brandNoBrand id, name or domain (from list_brands). Optional when the account has a single brand.
limitNoMax items to return (default 10, max 50).
engineNoOptional AI engine filter, comma separated: chatgpt, gemini, perplexity, ai_overviews, ai_mode. Default: all engines.
offsetNoItems to skip, for pagination.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description adds useful output composition details (ranking by lost-answer frequency, matching action-plan item) but does not disclose any additional behavioral traits such as authentication needs, rate limits, or side effects.

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?

Two sentences, both dense and purposeful. The first front-loads what is returned and how it is ranked; the second justifies the tool's value. There is no filler or repetition.

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?

With no output schema, the description adequately explains the return values: third-party sites/pages, their ranking basis, and the associated action-plan item. All seven parameters are fully documented in the schema, and annotations cover safety, so nothing critical is missing for an agent to call this correctly.

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 the schema already fully documents all seven optional parameters (date range, brand, language, limit, offset, engine). The description adds no parameter-level meaning beyond what the schema provides, making the baseline 3 appropriate.

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 specific resource — third-party sites and pages cited in answers the brand loses — and a precise scope condition (competitor named, brand not). This distinguishes it from a generic top-sources tool and tells the agent exactly what domain the result covers.

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?

Provides clear context for when to use it: finding the shortest path back into lost answers by getting listed on the cited sites. It does not, however, name alternative tools (e.g., get_top_sources or get_action_plan) or state when not to use it, so it falls short of explicit when/when-not 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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