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Howseen

by ai.howseen
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Get changes

get_changes
Read-only

What changed between the last two completed scans (or since a date): prompts gained and lost, visibility delta per engine, tracked competitors newly named, and the likely causes (sources that started or stopped citing the brand).

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_changes"
  }
}

Input Schema

NameRequiredDescriptionDefault
brandNoBrand id, name or domain (from list_brands). Optional when the account has a single brand.
sinceNoOptional YYYY-MM-DD: compare the latest scan with the last scan on or before this date. Default: the previous scan.
engineNoOptional AI engine filter, comma separated: chatgpt, gemini, perplexity, ai_overviews, ai_mode. Default: all engines.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds real behavioral value by describing the comparison window and default behavior ('last two completed scans' / default previous scan), plus the causal attribution content, which goes beyond the annotations.

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?

One dense sentence that is front-loaded with the core purpose and then enumerates return contents; every clause carries information, though the parenthetical cause clause makes it slightly heavy for a single sentence.

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 usefully enumerates what comes back (gains/losses, deltas, competitors, causes), which compensates well. It stops short of describing pagination or response structure, but nothing needed to call the tool correctly is missing.

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 all three params (brand, since, engine) are already documented in the schema. The description reinforces the date-comparison semantics ('since a date') and the per-engine breakdown but adds no syntax or format detail beyond the schema. Baseline 3 applies.

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 verb+resource with scope: 'What changed between the last two completed scans (or since a date)', then enumerates the exact outputs (prompts gained/lost, visibility delta per engine, newly named competitors, likely causes). An agent can distinguish this from get_visibility and get_prompt_gaps without opening a 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 clear context for when to use it — comparison between the last two completed scans, or against a supplied date — but names no alternatives or exclusions (e.g., when to prefer get_visibility or get_prompt_gaps instead).

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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