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MisarSEO MCP Server

get_brand_scan_trend

Read-onlyIdempotent

The recorded AI-visibility history for one brand or domain: mentions, cited sources and competitors seen at each past Brand Radar scan, oldest first. Answers whether visibility in AI answers is moving, which a single run_brand_radar_scan cannot. Returns only scans that actually ran — empty for a target never scanned, filling in as scans run, with nothing interpolated or back-filled. FREE — reads recorded scans, charges no credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceNoInclusive lower bound, YYYY-MM-DD.
targetYesBrand or domain, matched case-insensitively against past scans.
projectIdYesRequired. The MisarSEO project ID to scope this call to. Get one from list_projects.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), yet the description still adds real behavior: no interpolation or back-filling, only scans that actually ran are returned, oldest-first ordering, and an explicit billing statement ('FREE — charges no credits').

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?

Three sentences, front-loaded with what is returned before the comparison and the caveats. Each clause carries distinct information — payload, contrast with the sibling, empty/fill-in behavior, cost.

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 carries the return-shape burden and does it reasonably well: it names the fields seen per scan and the ordering, and explains empty results as scans accumulate. It stops short of stating volume limits or pagination, a minor gap for a history endpoint.

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 target matching semantics, the YYYY-MM-DD pattern for since, and the projectId provenance ('Get one from list_projects') are already documented. The description adds no parameter-level detail beyond that, which is the expected baseline when the schema does the work.

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 and resource ('recorded AI-visibility history for one brand or domain') and enumerates the payload ('mentions, cited sources and competitors'), plus the ordering ('oldest first'). It is immediately distinguishable from run_brand_radar_scan and from the status sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly names the alternative and the condition that selects it: 'Answers whether visibility in AI answers is moving, which a single run_brand_radar_scan cannot.' It also sets a when-not expectation by noting the result is empty for a target never scanned.

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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