search_tv_modelsFind which TV or monitor models whatmount.com has published mount facts for, by brand, model fragment or screen size. Returns up to 10 with their facts and page URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Brand, model fragment or size, e.g. "Hisense 65" or "TCL Q6" |
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?
Annotations already capture the safety profile (read-only, idempotent, non-destructive, not open-world). The description adds useful behavioral detail beyond annotations: it caps results at 10 and states each result includes facts and page URLs. This exceeds the baseline but isn't exhaustive about matching semantics or empty-result behavior.
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 sentences, about 28 words, with the action and scope front-loaded and the result behavior stated succinctly. Every clause adds information; there is no filler or repetition.
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?
The tool is simple (one free-text parameter), annotations cover behavioral safety, and the description explains the return payload ('up to 10 with their facts and page URLs'), which is necessary since no output schema exists. The definition gives an agent enough to invoke it correctly.
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%: the query parameter is already documented with examples ('Hisense 65' or 'TCL Q6'). The tool description largely restates the same query types ('brand, model fragment or screen size'), adding no new format or syntax guidance, so the high schema coverage baseline of 3 applies.
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 ('find') and names the exact resource ('TV or monitor models whatmount.com has published mount facts for'), plus the search dimensions (brand, model fragment, screen size). This clearly distinguishes it from sibling tools like list_models_by_vesa_pattern or lookup_tv_mount_specs, which operate on different lookup keys.
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 states clear context: use when you need to discover covered models by brand, model fragment, or screen size. It does not explicitly contrast with sibling tools or provide exclusion criteria, so it misses the top anchor for explicit when/when-not 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.
Each tool targets a distinct query mode: reverse lookup by VESA pattern, exact model specification lookup, and flexible model search. The slight overlap in returned specs is mitigated by clear input differences (model number vs brand/fragment/screen size).
All tool names follow a consistent verb_noun pattern in lowercase snake_case: list_models_by_vesa_pattern, lookup_tv_mount_specs, and search_tv_models. The verbs are semantically distinct and the object naming is uniform.
Three tools is at the lower end of the ideal range, but this is a narrowly scoped reference server and each tool serves a necessary, non-redundant purpose. No filler or overlapping tools are present.
For a read-only factual lookup service, the surface covers the main entry points: search by model/brand/size, exact model specification lookup, and reverse lookup by VESA pattern. There are no obvious dead ends for the domain.