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get_competitive_landscape

Read-only

Who is taking this site's search traffic. Returns rivals, how many of the site's keywords each takes, and their pages per funnel stage against the site's own — e.g. six competitor bottom-of-funnel pages against your one. Free. Check the depth field before trusting detail: "serp" means real per-keyword rivals, "known" means we know who competes but not on which terms, "none" means nothing on file. Note it reports rivals ranked ABOVE the site, not the whole results page.

Input Schema

NameRequiredDescriptionDefault
detailNoOutput verbosity: "concise" (default) trims long lists to top-25 and caps size; "detailed" returns the full result.
site_idYesThe site ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare read-only, open-world, non-destructive. Beyond that the description discloses genuinely useful traits: the cost model ('Free'), the meaning of each depth value ('serp'/'known'/'none'), and the critical scope caveat that it reports only rivals ranked ABOVE the site rather than the full results page. That scope caveat materially changes how an agent should interpret results.

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?

Purpose is front-loaded in the first sentence, followed by output summary, cost, interpretation caveat, and scope limitation in descending priority. Every sentence adds information, though the funnel-stage example adds length without much decision value.

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 burden of describing returns, and it does: rivals, keyword counts, funnel-stage page comparisons, plus the depth-field semantics. Combined with the scope caveat, an agent has enough to call and interpret it correctly, though pagination/verbosity interaction with the detail param is unaddressed.

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 both parameters (detail, site_id) are already documented structurally. The description's 'depth' explanation refers to a returned output field, not an input parameter, so it adds no parameter-level meaning. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific framing ('Who is taking this site's search traffic') and enumerates the concrete outputs: rivals, keyword counts per rival, and funnel-stage page comparisons. It distinguishes itself from generic competitor siblings by scope (rivals ranked above the site), but never names an alternative sibling like discover_competitors or get_competitor_keyword_overlap.

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

Usage Guidelines3/5

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

Gives interpretive guidance ('Check the depth field before trusting detail', 'Free', and the caution that rivals are only those ranked above), which implies intended use. However it never states when to reach for this versus neighboring tools, and no explicit when-not guidance is provided.

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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