Test a saved capability binding or preview-test an unsaved one.
| Name | Required | Description | Default |
|---|---|---|---|
| scope | No | ||
| config | No | ||
| scope_ref | No | ||
| binding_id | No | ||
| profile_id | No | ||
| provider_id | No | ||
| execution_owner | No | ||
| customer_metadata | No |
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?
No annotations are provided, so the description must fully disclose behavioral traits. It only states the high-level action without revealing side effects, authentication needs, rate limits, or any constraints. The lack of detail leaves the agent uncertain about the tool's impact (e.g., does testing create audit logs or trigger executions?).
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, efficient sentence with no redundancy. Every word adds value, and the two use cases are presented succinctly without unnecessary elaboration.
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 the complexity (8 parameters, no output schema, no annotations), the description is far too brief. It provides no information about return values, error conditions, or parameter relationships. The agent lacks sufficient context to use the tool reliably.
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 description does not mention any of the 8 parameters. With 0% schema description coverage, the agent has no guidance on how to populate scope, config, binding_id, etc. This is a critical gap for a tool with many parameters, making correct invocation nearly impossible.
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 uses a specific verb 'Test' and clearly identifies the resource 'capability binding'. It distinguishes two distinct use cases: testing a saved binding and preview-testing an unsaved one, which differentiates it from siblings like create_capability_binding or list_capability_bindings.
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 explicitly states the two contexts for use (saved vs unsaved), giving clear when-to-use guidance. However, it does not mention when not to use the tool or suggest alternatives, leaving the agent to infer from sibling names.
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.
Most tools target distinct resources or actions, but there is some overlap (e.g., run_repository_fix vs run_repository_pipeline vs simulate_repository) that could cause confusion. Overall, descriptions help differentiate.
Tool names are primarily snake_case with a verb_noun pattern, but there are inconsistencies (e.g., single-word verbs like 'simulate', 'tokenize', and mixed prefixes like 'preview_', 'product_'). The pattern is readable but not uniform.
With 140 tools, the server is extremely over-scoped for typical MCP usage. This overwhelms agents and suggests poor separation of concerns, likely violating the principle of minimal tool surfaces.
The tool set covers a wide range of functionalities including data onboarding, simulation, decisions, repository management, and admin operations. Minor gaps exist (e.g., no update_agent_run), but core workflows are well-supported.
