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Glama

rail_get

Rail — one entry with notes and cross-links.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

C2.1/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of explaining behavior. It mentions that the result contains notes and cross-links, but it does not state that the operation is read-only, what happens for missing or invalid ids, or any error or output behavior.

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

Conciseness2/5

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

The text is brief and front-loaded, but the brevity removes essential information rather than being appropriately concise. A short fragment without a verb or usage context is under-specified.

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

Completeness2/5

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

For a tool with no annotations, no output schema, and a single undocumented parameter, the description leaves too much implicit. It does not connect rail_get to rail_search, clarify id semantics, or describe the returned entry beyond two attributes.

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

Parameters1/5

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

The schema only defines id as a required string and the description does not explain what id refers to or how it identifies the entry. With 0% schema description coverage, the description provides no compensating parameter guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource ('Rail') and indicates a single-entry result, but it lacks an explicit verb such as 'get', 'returns', or 'retrieves'. It does not clearly distinguish from rail_search, so the intended action must be inferred from the tool name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to call rail_get versus rail_search or other sibling tools. The phrase 'one entry' implies fetching by identifier, but no explicit when-to-use, prerequisites, or alternatives are provided.

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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TDQS

C2.4/5.0
Disambiguation4/5

Most tools are cleanly separated by entity prefix and action (_get vs _search), so AWARE/Box/etc are not easily confused. The main ambiguity is among spl_lab_auth, spl_agent_key, and spl_signup, which all relate to account/key creation and could cause misselection.

Naming Consistency3/5

The 24 entity tools follow a consistent <entity>_get/<entity>_search pattern, which is predictable and readable. However, the five spl_* tools mix noun-style names like spl_catalog with verb-style names like spl_discover and spl_signup, creating a noticeable second convention.

Tool Count2/5

At 29 tools, the server exceeds the comfortable 3-15 range and even the heavier 16-25 range. The 12 get/search pairs are systematic, but combined with the five spl_* tools the overall surface feels bloated and harder to scan.

Completeness4/5

For a retrieval-oriented knowledge server, every entity has both point lookup and free-text search, plus lab signup, agent key minting, and discovery/catalog resources. Minor gaps like no key revocation or list-all operations are not critical for the stated purpose.

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