list_script_snippetsList the project's reusable pre-request and post-response script snippets, with their code and how often each is used. Requires project context.
| Name | Required | Description | Default |
|---|---|---|---|
| skip | No | Number of snippets to skip (for pagination, default 0) | |
| take | No | Number of snippets to return (default 50, max 100) | |
| searchTerm | No | Filter by name or description containing this text |
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 signals a safe read operation, so the description adds value by noting the need for project context and the inclusion of code and usage counts. It does not contradict the annotations, but it does not go deeper into behavior such as pagination limits or ordering beyond the schema parameters.
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 a single, compact sentence that front-loads the tool's purpose and immediately communicates the key output fields. Every phrase adds relevant information with no wasted words.
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 read-only list operation with three simple, fully documented parameters, the description is largely complete: it names the resource, the output content, and a required precondition. It could be slightly richer by describing the expected return shape or pagination behavior, but with the schema covering parameters, the gap is minor.
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?
Schema description coverage is 100%, with skip, take, and searchTerm all clearly documented. The tool description adds no parameter-specific meaning beyond the schema, so the baseline of 3 is appropriate.
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 states a specific verb ('List') and resource ('reusable pre-request and post-response script snippets') and adds what is returned: code and usage frequency. This clearly distinguishes it from sibling tools like list_doc_snippets or get_doc_snippet by naming the exact resource type.
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 by defining its purpose, and it provides a useful prerequisite ('Requires project context'). However, it does not explicitly mention alternatives or state when not to use this tool versus sibling list/get tools.
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.