obtener_entrevista
Obtiene el contenido completo de una entrevista publicada por su slug (o slug_en).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
Obtiene el contenido completo de una entrevista publicada por su slug (o slug_en).
| Name | Required | Description | Default |
|---|---|---|---|
| slug | 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?
No annotations exist, so the description carries the full burden. The verb 'obtiene' implies a read-only operation, and 'contenido completo' clarifies the extent of data returned. However, it does not disclose error responses, not-found behavior, or any potential side effects. More transparency would be beneficial, but the core behavior is reasonably clear.
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 that immediately states the action, target, and parameter format. There is no redundancy or filler; every word contributes to understanding.
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 get-by-slug tool with one parameter and no output schema, the description adequately explains that it retrieves complete interview content. It doesn't explain response structure or errors, but given the tool's simplicity, this is a minor gap. It is complete enough for most use cases.
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 schema only lists 'slug' as a string with no description (schema coverage 0%). The description adds critical meaning by stating that the slug can be either 'slug' or 'slug_en', which is not obvious from the schema. This compensates for the schema's lack of detail.
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 ('obtiene' - obtains), clearly identifies the resource ('entrevista publicada' - published interview), and specifies the scope ('contenido completo' by 'slug o slug_en'). It distinguishes this from sibling obtener_* tools that target different entities (entidad, evento, etc.).
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 usage when you have a slug or slug_en and need the full interview, but it does not explicitly state when to use this vs alternatives like buscar_entrevistas or other obtener_* tools. No exclusion criteria or alternative naming is provided; usage is inferred from the tool's purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.