get_contract_summaryGet contract test coverage summary for a test suite. Shows how many test cases are linked to spec endpoints, how many have schema drift, and overall endpoint coverage. Requires project context.
| Name | Required | Description | Default |
|---|---|---|---|
| testSuiteId | Yes | Public ID (GUID) of the test suite |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already establishes that this is a safe read operation. The description adds context about the output content and the project-context requirement, but it does not disclose error conditions, data freshness, or other behavioral details. No contradiction with annotations exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences deliver the purpose, the output contents, and a key prerequisite without repetition or filler. The most important information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only summary tool with one well-documented parameter, the description is nearly complete. It explains what the summary contains, which compensates for the lack of an output schema, though it could be slightly clearer about what 'project context' means and how it should be established.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter testSuiteId is fully described in the schema as the public ID (GUID) of the test suite. Since schema description coverage is 100%, the description does not need to add parameter details, and it adds none beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific resource ('contract test coverage summary') and enumerates what it shows: linked test cases, schema drift, and endpoint coverage. It is clear and informative, but it does not explicitly distinguish itself from siblings like get_contract_drift or get_schema_drift_report.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when a contract test coverage summary for a test suite is needed. It also notes 'Requires project context,' which is a useful prerequisite, but it offers no explicit guidance on alternatives or when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.