Skip to main content
Glama

Manotr

get_product

Full detail for one Manotr product: what it does, who it is for, how it deploys, and its FAQ.

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": {
      "slug": "<slug>"
    },
    "name": "get_product"
  }
}

Input Schema

NameRequiredDescriptionDefault
slugYesOne of: news-agent, media-pipeline, triveni, openmailbot, filebot, proactiveguard.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the burden alone. It usefully discloses the shape of the returned content (description, audience, deployment, FAQ), which implies a read-only lookup, but it says nothing about error behavior for an unknown slug or whether the payload is a single object versus nested sections.

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?

One compact sentence with the resource stated first and the returned content enumerated after, so it is front-loaded and waste-free. The fragment lacks an explicit verb, which costs it a little crispness.

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?

For a simple one-parameter read tool with no output schema, the description covers enough to call it correctly and gives a preview of returned fields. However, with no annotations to lean on, the omission of failure behavior and response shape leaves a modest gap.

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?

The single slug parameter is fully documented in the schema, including the enumerated accepted values, so the schema already does the heavy lifting. The description adds no extra meaning about slug format, case sensitivity, or what happens on an unrecognized value, which is the baseline expectation at 100% coverage.

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?

The description names a specific resource ('one Manotr product') and enumerates the payload (what it does, who it is for, how it deploys, its FAQ), which makes it clearly the single-record detail tool. It stops short of naming the sibling it differs from, but 'one product' implicitly separates it from list_products and search_manotr.

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?

Usage is only implied: an agent must infer it should call this after it already knows a specific product slug, presumably from list_products or which_product. There is no explicit when-to-use, when-not-to-use, or alternative routing statement.

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