Get full details for a single daycare by slug, including capacity by age band (infant / toddler / 2s / 3s / 4s / pre-K / kindergarten) when the daycare has filled it in. Use after search_daycares to surface specifics.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Daycare slug from search_daycares results. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that capacity by age band is only present 'when the daycare has filled it in', a key behavioral detail. Without annotations, the description carries full burden; it adequately covers the read nature but could mention response structure or pagination implications, though none apply here.
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 punchy sentences: first states purpose and key data, second gives usage guidance. No wasted words; front-loaded with essential action and resource.
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?
Despite lacking output schema, the description explains the return includes 'full details' and lists capacity fields. Combined with usage order hint, it provides sufficient context for correct invocation and interpretation for a simple get operation.
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 sole parameter 'slug' is described as 'Daycare slug from search_daycares results', adding practical context beyond the schema's own description. This clarifies the source and expected format, fully leveraging schema coverage.
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?
Clearly states 'Get full details for a single daycare by slug', specifying the verb, resource, and unique identifying field. Differentiates from sibling tools like 'search_daycares' by emphasizing singular detail retrieval rather than list search.
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 instructs 'Use after `search_daycares` to surface specifics', providing clear context for when to apply this tool versus alternatives like 'search_daycares' or 'daycare_capacity'.
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.
Tools are clearly grouped by prefix (admin_, daycare_, org_, parent_) and within each group have distinct, non-overlapping purposes. For example, parent_add_kid vs parent_remove_kid are unambiguous.
All tools follow a consistent snake_case pattern with role prefix and action_noun structure. Minor exceptions like 'nearby_programs' are standalone and do not disrupt the overall consistency.
With 72 tools, this is far beyond the typical well-scoped range of 3-15. While the tools cover multiple user roles, the count is excessive and likely overwhelming for an agent, falling into the 'too many' category.
The tool set covers most core workflows for parents, orgs, and admins, but notable gaps exist: there is no tool to create a program or daycare, and admin tools for approving pending claims or discoveries are missing, leaving dead ends.
