list_project_style_guide_rulesList the style guide rules as they apply in this project: the built-in default, the organization override, the project override and the effective severity of each, plus the organization's custom rules. Use get_style_guide_rules for the organization-level view. Requires project context.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 indicates a read-only operation, but the description adds the behavioral requirement of needing project context. This extra note is useful, though there is no mention of potential errors or side effects beyond that.
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, two sentences, with the action and scope front-loaded. It provides specific details about what is included without any unnecessary filler, making it easy to parse quickly.
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?
Given there is no output schema, the description sufficiently describes what the tool returns (built-in default, org override, project override, effective severity, org custom rules). It also mentions the prerequisite of project context and directs to the org-level alternative, covering key contextual information.
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 tool has no parameters and the schema is fully covered (empty). The description adds no parameter-level detail, which aligns with the baseline for high schema coverage. The purpose-level detail does not specifically enhance parameter understanding because there are no parameters.
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 lists style guide rules as they apply in the project, enumerating the built-in default, organization override, project override, effective severity, and organization custom rules. This makes the purpose specific and distinguishable from the related org-level tool.
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?
It explicitly directs users to get_style_guide_rules for the organization-level view, which helps with tool selection. It also mentions the requirement for project context. However, it does not contrast with the sibling list_custom_style_guide_rules, which could have provided additional selection guidance.
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.