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thein-art

mcp-server-peecai

by thein-art

Domain Citation Report

get_domains_report
Read-onlyIdempotent

Retrieve domain analytics report with metrics like retrieval rate, citation rate, and retrieved percentage. Filter by classification, date, and dimensions for tailored analysis.

Instructions

Get domain analytics report: retrieval_rate, citation_rate, and retrieved_percentage. Classification values: OWN, CORPORATE, COMPETITOR, EDITORIAL, REFERENCE, INSTITUTIONAL, UGC, OTHER. Returns up to limit results (default: 100). Classification is filtered client-side after retrieval. Use filters array for server-side filtering by model, tag, topic, prompt, domain, URL, or country_code. Without date filters, returns data across all available dates. Empty results may indicate the project has no report data for the given time range or filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idNoProject ID (uses PEECAI_PROJECT_ID env if omitted). Call list_projects to find IDs.
start_dateNoStart date (YYYY-MM-DD). Omit for no lower bound.
end_dateNoEnd date (YYYY-MM-DD). Omit for no upper bound.
dimensionsNoBreakdown dimensions. Each adds a grouping level to results: prompt_id (by search prompt), model_id (by AI model), model_channel_id (by model channel, e.g. openai-0/perplexity-0), tag_id (by category tag), topic_id (by topic group), date (by date), country_code (by country), chat_id (by individual chat). Multiple dimensions can be combined.
classificationNoFilter by domain classification (applied client-side after retrieval).
filtersNoServer-side filters. Multiple filters are AND'd together.
limitNoMax results (1-10000, default: 100)
offsetNoResults to skip
Behavior5/5

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

Annotations indicate read-only, non-destructive, idempotent behavior. The description adds important behavioral details: classification is filtered client-side after retrieval, filters are server-side AND'd, and date range omission returns all data. No contradictions.

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?

Two paragraphs: first states purpose, second covers filtering and edge cases. Fairly concise and front-loaded. Minor redundancy in classification list (already in schema enums) but acceptable.

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?

Despite no output schema, the description explains core metrics and behaviors (client/server filtering, date ranges, limit/offset). It briefly mentions empty results. Enough for an agent to use correctly, though output structure could be clarified.

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

Parameters4/5

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

Schema coverage is 100% with descriptions for all 8 parameters. The description adds value by clarifying client-side classification filtering and the server-side filter structure (AND logic). This exceeds the baseline of 3.

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 clearly states it retrieves domain analytics with specific metrics (retrieval_rate, citation_rate, retrieved_percentage) and lists classification values. It distinguishes from sibling tools like get_brands_report or get_urls_report by focusing on domain-level data.

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?

The description explains client-side vs server-side filtering, date range behavior, and empty result interpretation. It lacks explicit alternatives or when-not-to-use guidance, but provides sufficient context for typical usage.

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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