angel_searchBusca servicios, experiencia, metodología y casos públicos de Ángel Moncada. Devuelve coincidencias con URLs canónicas.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| metadata | Yes |
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 and idempotentHint annotations already cover the safety profile; the description adds that results are matches with canonical URLs and scope is public content. It does not reveal behavior such as pagination, result ordering, or empty-result handling, so it adds only modest context beyond the annotations.
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 short sentences with the core behavior first and the output characteristic second. Every clause adds information and there is no filler.
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 two-parameter search tool with a read-only/idempotent annotation and an output schema, the description covers the main user intent and the output shape. It could be more complete with explicit guidance on when to choose this tool over direct siblings, but is not critically incomplete for invocation.
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%, but the two parameter names are self-explanatory: 'query' is the search text and 'limit' caps result count. The description reinforces the meaning of query by saying it searches services, experience, methodology, and cases, though it adds no detail about limit or query formatting.
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 action ('Busca') over a defined set of resources: services, experience, methodology, and public cases of Ángel Moncada. It also states the output form ('Devuelve coincidencias con URLs canónicas'), which distinguishes this search tool from the targeted sibling getters and listers.
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 the tool is for cross-cutting search across the knowledge base, but it does not explicitly say when to prefer it over angel_get_*, angel_list_cases, or angel_recommend_service. The sibling names give context, yet the description itself leaves the choice to inference.
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 aspect of the public consulting domain: contact, methodology, profile, individual service details, case list, service recommendation, and cross-cutting search. The overlap between search and get_service is minimal because search returns matches with canonical URLs while get_service provides the full approved description of a specific service.
All tool names follow a consistent pattern: the prefix 'angel_' plus a clear verb ('get', 'list', 'recommend', 'search') followed by the target noun. This uniform verb_noun convention makes the tool set highly predictable and easy to navigate.
With 7 tools, the server is well-scoped for a consulting information and recommendation service. Each tool earns its place, covering both direct lookups (contact, profile, service, methodology) and discovery/guidance (list cases, recommend, search).
The domain of public consulting information is well covered: profile, methodology, services, cases, contact, and search are all present. A minor gap is the absence of a dedicated 'list_services' tool—an agent must rely on search or recommendation to discover available services—but this is not a fatal omission given the search capability.