Skip to main content
Glama

Read the AI Shelf

read_ai_shelf
Read-onlyIdempotent

Product recommendations in AI answers. Without a target, lists categories and products; with one, its visibility, share of shelf and who holds the shelf.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
target_idNo
project_idYes
target_kindNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds genuine behavioral value beyond that: the output mode changes depending on whether a target is supplied (listing categories/products vs returning visibility, share of shelf, and shelf holder). It stops short of describing pagination or return shape.

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 short sentences, front-loaded with the domain concept before the mode behavior. No wasted words, though the terse phrasing makes the target/target_kind relationship slightly ambiguous.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description does a fair job explaining the dual output modes. But for a 3-param tool with 0% schema coverage, it omits the required project_id and the distinction between target_id and target_kind, which an agent needs to invoke 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 coverage is 0%, so the description must carry the load. It conveys the central role of 'target' (list mode vs detail mode) which maps to target_id, and 'categories and products' echoes the target_kind enum. But it never mentions project_id (the required param) or names target_id/target_kind explicitly, leaving meaningful gaps.

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?

States a specific resource ('product recommendations in AI answers') with the read semantics carried by the name/title. It distinguishes itself reasonably from the many read_visibility_* siblings by focusing on product recommendations and shelf share. It doesn't explicitly name a sibling it is not, so it falls short of a 5.

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?

It explains the two operating modes via the presence or absence of a target ('without a target... with one...'), which is useful invocation context. However, it gives no when-to-use vs alternatives guidance and never names which sibling to prefer for related questions.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources