get_podcast_episodeDetalhe completo de um episódio: áudio (URL .mp3), excerpt, convidados, tópicos, links citados e transcrição (quando disponível).
| Name | Required | Description | Default |
|---|---|---|---|
| episode_slug | Yes | Slug do episódio. | |
| podcast_slug | Yes | Slug da série. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the return content but does not mention potential errors, authentication requirements, or side effects. Adequate but not comprehensive.
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?
Single sentence with no wasted words. Front-loaded with the core purpose.
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 retrieval tool with two parameters and no output schema, the description covers the key return fields. Lacks mention of error cases but is generally complete enough.
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 coverage is 100% with descriptions for each parameter. Description adds no additional meaning beyond the schema; it focuses on output rather than parameters.
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?
Description clearly states it provides complete details of an episode, listing specific data fields (audio URL, excerpt, guests, topics, links, transcript). Differentiates from sibling list tools.
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?
No explicit when-to-use or when-not-to-use guidance. Usage is implied from the tool name and description, but given sibling list tools, explicit guidance would help.
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 has a clearly distinct purpose: course availability vs upcoming classes, detailed vs summary listings, separate tools for blog, podcast, services, teachers, radio, school info, and cross-content search. No overlapping tool descriptions.
Most tools follow a verb_noun pattern (list_, get_, check_), but 'radio_now_playing' and 'school_info' deviate slightly, and 'search' is a single verb. Nonetheless, the naming is mostly consistent and predictable.
15 tools is well-scoped for a school information server covering courses, blog, podcast, radio, services, teachers, and institutional info. Each tool serves a necessary function without redundancy.
The tool surface provides comprehensive coverage for informational queries about the school: all major content types (courses, blog, podcast, radio) have list/detail tools, real-time availability, search, and institutional info. No obvious gaps for a read-only knowledge server.