get_mock_rule_diagnosticsInspect one mock rule. view 'drift' (default) compares the rule against the latest published spec version and lists what changed since it was pinned; view 'state' returns the stored state of a stateful rule. Requires project context.
| Name | Required | Description | Default |
|---|---|---|---|
| view | No | What to inspect: 'drift' (default) or 'state' | drift |
| ruleId | Yes | The public Id (Guid) of the mock rule |
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?
Beyond the readOnlyHint annotation, the description explains the two operational modes: comparing against the latest published spec for drift and returning stored state. This gives concrete behavioral detail without conflicting with the read-only nature.
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 two sentences, dense and free of fluff. It front-loads the main purpose and efficiently explains the two view options and the context requirement.
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 inspection tool, the description covers the key behavioral aspects (drift vs. state) and the prerequisite. It does not describe output format, but given no output schema and the tool's simplicity, this is a minor gap rather than a significant omission.
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 schema already fully covers both parameters with descriptions ('What to inspect' and 'The public Id (Guid)'). The tool description restates the view semantics but adds no new parameter-specific meaning beyond what the schema provides.
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 the tool's function: 'Inspect one mock rule.' This is a specific verb and resource, and the singular 'one' distinguishes it from list_mock_rules and other sibling tools that operate on multiple rules.
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 use when needing to inspect a single mock rule's drift or state, and notes the prerequisite 'Requires project context.' However, it does not explicitly contrast with sibling tools like get_mock_server or preview_smart_mock, leaving some inference to the user.
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.