list_shared_responsesList the reusable responses of the shared library. Scope 'project' (default) reads the current project's library, 'org' the organization-wide one. Each entry carries the id and rowVersion needed to update or link it.
| Name | Required | Description | Default |
|---|---|---|---|
| scope | No | Which library to read: 'project' (default) or 'org' | project |
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 read-only operation, and the description adds useful behavioral context by noting that each entry includes the id and rowVersion needed for subsequent updates or linking. It does not describe response format or pagination, but the added detail about returned fields is valuable 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 well-structured, consisting of two sentences that efficiently convey the tool's purpose and the key parameter. No redundant or extraneous information is included.
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 listing tool, the description covers the essential context: what is listed, how the scope works, and what data is returned (id and rowVersion). It doesn't include output schema details, but that is not necessarily required for a read-only list operation, and the given information is sufficient for an agent to decide to use it.
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 'scope' parameter is fully described in the schema with its type, default value, and allowed values ('project' or 'org'). The description reinforces the meaning, making the parameter semantics exceptionally clear and complete.
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 a specific verb ('List') and resource ('reusable responses' of the shared library), and the scope parameter distinguishes this from related tools like 'get_shared_response' and 'list_shared_schemas'. It precisely conveys what the tool does without ambiguity.
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 explains when to use the tool: to list reusable responses from either the project or organization library, with the scope parameter clarifying the context. It also hints at the purpose of the returned data (id and rowVersion for updates/links), but does not explicitly contrast with alternatives; however, the purpose is clear enough given the sibling list.
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.