read_registryRetrieve model-registry entries for a profile, optionally filtered by model ID, to inspect roles, scores, best params, and last tested. Trimmed by default; verbose adds timestamps.
Read model-registry entries (roles, scores, best params, last tested) for a profile, optionally filtered to one model_id. Trimmed by default; verbose includes timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
| profile | Yes | ||
| verbose | No | ||
| model_id | No |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the burden of behavioral disclosure. It adds useful behavior by stating that output is 'Trimmed by default; verbose includes timestamps,' and the verb 'Read' implies no mutation. However, it does not disclose error behavior, whether a missing profile/model_id is tolerated, or output shape limitations.
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?
Two tight sentences front-load the core action and resource, then add optional filtering and output-format details. No filler or redundant restatement of the tool name appears.
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 read operation with no output schema, the description covers the purpose, parameters, and key behavioral nuance (trimming/verbose). It could be more complete by noting what happens when no entries match or when the profile does not exist, but nothing essential to invoking the call correctly is missing.
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 0%, and the description compensates by assigning meaning to all three parameters: profile selects the registry context, model_id filters to one entry, and verbose expands timestamps. It adds semantic value beyond the bare string/boolean schema types, though requiredness of profile is left implicit.
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 names a specific verb ('Read'), a concrete resource ('model-registry entries'), and lists the entry fields (roles, scores, best params, last tested). It states the profile scope and optional model_id filtering, making it clearly distinct from siblings like write_registry_entry.
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 clearly identifies what data the tool operates on and the available scoping (profile, optional model_id), which tells an agent when this is the right read call. It does not explicitly name alternatives or exclusion criteria, but the read-versus-write contrast with siblings is implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.