Rempa

List products

list_products

Read-only

List the products a project tracks (products add-on), each asked on its own buyer questions: per product, its id, name, category, page, how often it is updated, whether it is active or paused, and from its latest update its visibility (share of the answers to questions that do not name it where AI names it), average position among the products named, sentiment (0 to 100) and the competing product named most (or the main competitor the brand picked). Also the account's product billing. Use it for "how are our products doing in AI answers?". Read-only.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project": "<project>"
    },
    "name": "list_products"
  }
}

Input Schema

Name	Required	Description	Default
`project`	Yes	The project: its id or its address (for example "acme-france"), as returned by list_projects.

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 4, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the trailing 'Read-only.' merely restates that, earning no credit. The description does add real behavioral context the annotations lack: it flags a prerequisite ('products add-on'), defines visibility precisely, and gives the sentiment range (0 to 100) plus fallback logic for the top competitor. It omits pagination, result limits, and behavior when the add-on is absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose and add-on prerequisite are front-loaded, but the middle is one long run-on sentence that strings together every returned field with nested parenthetical definitions. The information is useful yet hard to scan, and the field list would be clearer as a structured enumeration.

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 must carry return-value semantics, and it does so thoroughly, including derived metrics like visibility, average position, sentiment, and top competitor. The main gap is operational detail such as pagination or empty-result behavior, which matters less for a single-project listing.

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% and the single 'project' parameter is already documented with id-or-address syntax and a reference to list_projects. The description adds nothing about the parameter beyond the schema, so the 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 verb and resource ('List the products a project tracks') and enumerates the per-product fields returned, so the agent knows exactly what this returns versus the singular get_product or the comparison tool compare_products. It never names a sibling explicitly, so differentiation is inferred from the plural/listing framing rather than stated.

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?

Provides a concrete usage trigger with the quoted question 'how are our products doing in AI answers?', which tells the agent what user intent selects this tool. It gives no when-not guidance and does not route to alternatives like get_product or compare_products when the user wants a single product or a comparison.

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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