Skip to main content
Glama
vantagemcp

vantage-mcp

by vantagemcp
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

analyze_citation_gap

Read-onlyIdempotent

Compare your page against the AI-cited answer for a keyword and get an ordered fix brief: rewrite instructions to close gaps and get cited. Shows what to change, not just what the winner looks like.

Instructions

Compare your own page's structure against the AI-generated answer actually cited for this keyword, and return a fix brief: ordered rewrite instructions for your page, not just a description of the winner. Use this to answer 'what should I change on this page to get cited' rather than only 'what does a winning answer look like'. Carry out the fix_brief on the user's page in their own words; it never contains the cited answer's text.

Read-only: no side effects, safe to retry. Costs 1 quota unit/call (free tier is 30 units/month shared across every metered tool, so up to 30 calls to this tool alone if nothing else is used that period).

Returns: {"keyword", "your_url", "winning" (structure of the AI-cited answer, same shape as analyze_citation_structure), "yours" (same structure computed for your_url, including its own "outline" and "has_table", with "num_links_out"/"linked_domains" standing in for source count), "gaps" (list of plain-English differences worth acting on), "possibly_missing" (heads from the winning outline whose key words mostly do not appear on your page; word matching, so check each before adding it), "fix_brief" (list of instructions, most important first: opening, number, list, sections, missing points, table, sources, then a reminder to write in your own words - or a "no structural change indicated" line when every check already matches - and always last, one off-site step drawn from the winning answer's source_mix: which community sites (Reddit, YouTube, X...) it cites, or which other sites to get mentioned on. Page shape gets a page into the running; being cited is decided mostly by what other sites say about the brand)}, or {"error"} if either side couldn't be fetched/parsed.

Use analyze_citation_structure instead if you just want the winning answer's shape, not a comparison against your own page. Use check_prompt_coverage first if you have several keywords and do not yet know which ones you are missing from - this tool is for one keyword you already know needs work.

Args: keyword: the topic/query to check, e.g. "best project management tool". your_url: full URL of your own page to compare, e.g. "https://example.com/best-project-management-tools". country: market to read the cited answer in, e.g. "Italy". Defaults to "United States". language: language code, e.g. "it". Defaults to "en". engine: "chat_gpt" (default), "gemini" or "perplexity": whose answer to compare your page against.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
engineNochat_gpt
countryNoUnited States
keywordYes
languageNoen
your_urlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.8.0
    • addedInput schema / properties / engine
      Added value: +{
+  "default": "chat_gpt",
+  "title": "Engine",
+  "type": "string"
+}
  2. Changed2 schema fields changedv1.7.0
    • addedInput schema / properties / country
      Added value: +{
+  "default": "United States",
+  "title": "Country",
+  "type": "string"
+}
    • addedInput schema / properties / language
      Added value: +{
+  "default": "en",
+  "title": "Language",
+  "type": "string"
+}
  3. Addedv1.5.2

TDQS

A5/5.0
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description adds valuable operational context: 'Read-only: no side effects, safe to retry. Costs 1 quota unit/call' and explains the quota tier. It also discloses return behavior, including the error case, the order of fix_brief items, and the fact that the brief never contains the cited answer's text. No annotation contradiction exists.

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?

The description is long, but it is dense and well-organized: purpose, alternative guidance, read-only/cost, return format, and args. The most important information is front-loaded, and every sentence contributes operational value. Given the absence of an output schema, the length is justified by complexity rather than padding.

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?

There is no output schema, so the description compensates by detailing the return object fields (keyword, winning, yours, gaps, possibly_missing, fix_brief, error case). It also covers parameter semantics, quota cost, and sibling-tool differentiation. For a complex comparison tool with two required parameters and three optional ones, nothing essential is missing for an agent to call and interpret it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description carries full responsibility for parameter meaning, and it succeeds. Each parameter is given a concise explanation with concrete examples (e.g., keyword: 'best project management tool'; your_url: 'https://example.com/best-project-management-tools'), plus defaults and engine options. This goes well beyond the bare schema.

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?

The description opens with a clear, specific action: compare your page's structure against the AI-cited answer and return a fix brief. It further distinguishes the tool by stating it provides ordered rewrite instructions for the user's page, not merely a description of the winning answer. This is a precise verb+resource statement that an agent can act on confidently.

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?

The description gives explicit routing guidance: use analyze_citation_structure when only the winning answer's shape is needed, and use check_prompt_coverage first for multi-keyword discovery. It also frames the tool's purpose as answering 'what should I change on this page to get cited' rather than only describing the winner. This leaves no ambiguity about when to choose this tool over siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools