list_servicesLista serviços oferecidos pela ER+ ALÉM dos cursos regulares: 'demo' (gravação de demo profissional com Ruy, R$ 350), 'mentoria' (mentoria 1:1 com Ruy, R$ 250/h), 'b2b' (treinamentos corporativos pra empresas). Use quando aluno perguntar sobre demo, mentoria, treinamento empresarial. Pra cursos regulares, use list_courses.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Filtra por tipo de serviço (opcional, default 'all'). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description fully discloses the tool's behavior: it lists services with types and prices. No hidden side effects or requirements are omitted.
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 concise: two sentences that front-load the purpose and then provide detailed examples and usage guidance. Every sentence adds value without unnecessary words.
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 list tool with one optional parameter and no output schema, the description provides complete context: services offered, their types, pricing, and when to use. No gaps.
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 covers 100% of the single parameter, but the description adds meaning by explaining the enum values ('demo', 'mentoria', 'b2b', 'all') and associating prices, which goes beyond the schema's minimal description.
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 clearly states what the tool does: it lists services offered by ER+ beyond regular courses, with specific examples (demo, mentoria, b2b). It distinguishes itself from sibling 'list_courses' by specifying it excludes courses.
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?
Explicitly tells when to use this tool (when a student asks about demo, mentoria, corporate training) and when not to (for regular courses, use list_courses). This provides clear selection criteria.
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.