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Privatrak

by com.privatrak
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AI reviews

list_reviews
Read-onlyIdempotent

The project's saved AI reviews (written by the customer's assistant with the product_review prompt), newest first, paged: scope with its page or funnel, key action (goal), title, period, confidence, when it was saved, and its recommendations counted by status (open, done, dismissed). Find the previous review of a scope here; read it in full with get_review.

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": "list_reviews"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNoPage number, from 1.
limitNoReviews per page, 1-100. Default 50.
projectNoProject ID, from list_projects. Required when this connection covers more than one project; may be left out when it covers one (and with an API key, which belongs to one project).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and closed-world, so the safety profile is covered. The description still adds real behavior: newest-first ordering, pagination, provenance (written by the customer's assistant with the product_review prompt), scope-by-page-or-funnel semantics, and the shape of recommendation counts by status. It does not mention rate limits or empty-result behavior, keeping it below a 5.

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?

Scope, ordering, and returned fields are front-loaded in the first sentence, with the get_review routing in the second. The parenthetical field enumeration is dense but earns its place since there is no output schema; minor tightening possible.

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?

With no output schema, the description carries the return-value burden and does so by enumerating the fields of each review entry and how recommendations are counted. Combined with the paging/ordering note and the pointer to get_review, an agent has everything needed to call this list tool correctly.

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 page, limit, and project are already documented, and the description adds only the general notion of paging and of scoping by page or funnel. It does not clarify how project selection combines with page/funnel scoping beyond what the schema says. Baseline 3 is appropriate.

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?

Specific verb-and-resource: lists the project's saved AI reviews, newest first and paged, and enumerates what each entry carries (scope, goal, title, period, confidence, saved time, recommendation counts). It also names the sibling that reads a single one in full (get_review), so an agent can separate it from get_review without opening the 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?

It clearly frames the browse/find use case ('Find the previous review of a scope here') and routes full reading to get_review. It stops short of explicit exclusions against adjacent siblings such as get_review_data or get_review_follow_up, so the alternative set is only partly covered.

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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