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List Linkable Endpoints

list_linkable_endpoints
Read-only

List the endpoints of an API spec that a test case can be linked to, with path, method and the version they come from. Use link_endpoint to establish the link. Requires project context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specIdYesPublic Id (Guid) of the API specification
versionIdNoPublic Id (Guid) of a specific spec version. Omit for the current one.

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

The readOnlyHint annotation already indicates this is a safe read operation, and the description's use of 'List' reinforces that. It adds useful context about the data being scoped to linkable endpoints and versions, but does not describe any potential side effects or edge cases. Since the annotation covers the key behavioral guarantee, this is adequate.

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

Conciseness5/5

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

The description is two concise sentences, with no filler or redundant information. It front-loads the primary purpose and then gives the essential workflow hint (use link_endpoint) and prerequisite (project context), making it efficient and easy to parse.

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?

There is no output schema, so the description's note that results include path, method, and version provides the core return information an agent needs. It also states the project-context prerequisite. It does not detail pagination or response envelope, but for a simple list operation the provided context is sufficient.

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?

Both parameters are already fully described in the schema, so the description does not need to repeat them. It does add that the returned endpoints include the version they come from, which loosely relates to versionId, but it does not clarify parameter usage beyond the schema. This meets the baseline for full schema coverage.

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?

The description clearly states the verb 'List', specifies the resource 'endpoints of an API spec that a test case can be linked to', and provides the output fields (path, method, version). This is distinct from the sibling list_endpoints tool, which would list all endpoints without the test-case-linking scope.

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?

The description tells the agent to use link_endpoint for the actual linking step, which is helpful workflow guidance. It also notes the prerequisite that project context is required. It does not explicitly contrast with list_endpoints, but the purpose is clear enough that an agent can decide when to use it.

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

A3.9/5.0
Disambiguation4/5

The tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.

Tool Count1/5

With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.

Completeness5/5

The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.

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