list_fixturesE84: List all project-owned fixtures in the active project. Fixtures are structured test data (YAML/JSON) reusable across tests, mocks and docs. Requires project context.
| Name | Required | Description | Default |
|---|---|---|---|
| skip | No | Number of fixtures to skip (default 0). | |
| take | No | Number of fixtures to return (default 50, max 100). | |
| tagFilter | No | Optional tag filter (comma-separated list is not supported — single tag only). |
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 communicates that this is a read-only operation, and the description's 'List' verb aligns with that. The description adds that project context is required, but it does not disclose potential errors, permission requirements, or other behavioral details beyond the annotation.
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?
The description is concise and front-loaded, with the primary action and scope in the first sentence. The second sentence defines fixtures and states the context requirement. There is no unnecessary repetition or fluff.
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?
The description covers the purpose, scope, and a prerequisite, and parameter schemas fully document the inputs. However, there is no output schema, and the description does not describe the response format or pagination behavior, leaving some context incomplete.
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?
All three parameters are documented in the schema with descriptions, so schema coverage is 100%. The tool description itself does not add extra parameter semantics, but per the rubric, high schema coverage establishes a baseline score of 3.
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 clearly states that the tool lists all project-owned fixtures in the active project. It uses a specific verb ('List'), identifies the resource ('fixtures'), and defines the scope ('project-owned', 'active project'). This distinguishes it from related tools like get_fixture or list_fixture_imports.
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 provides no explicit guidance on when to use this tool versus alternatives. It only mentions that project context is required, which is a prerequisite but not usage direction. No sibling tools are referenced for comparison.
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.