watch_programSets a fills-up/closing email alert for one program on the signed-in user’s Junely account — identical to the “alert me” button on junely.co. Only call when the user explicitly asks to be alerted. Requires connecting the user’s Junely account.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Program id from a search result |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint=true and destructiveHint=false, and the description adds that the tool sets an alert (mutation but idempotent). It also mentions sign-in required and identical to website button, which are helpful behavioral cues beyond 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?
The description is two sentences long, covering purpose, usage condition, and prerequisite without any fluff. The title also adds context (sign-in required). Every word earns its place.
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?
Given the low complexity (one parameter, no output schema, simple behavior), the description is complete. It includes the action, trigger condition, and authentication requirement, fully equipping the agent to decide and invoke correctly.
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 single parameter 'id' is fully described in the schema as 'Program id from a search result,' achieving 100% coverage. The description does not add much beyond this, meeting baseline expectations.
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 it sets a fills-up/closing email alert for one program, which is a specific verb+resource. It distinguishes itself from siblings like get_program_details (details retrieval) and search_programs (searching) by focusing on the alert action.
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 explicitly says 'Only call when the user explicitly asks to be alerted,' providing clear when-to-use guidance. It also mentions the prerequisite of connecting the user's Junely account, though it does not explicitly state when not to use or name alternatives.
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: get details, save to watchlist, search, set alerts, and view open programs. No overlapping functionality that could cause confusion for an agent.
Most tools follow a verb_noun pattern (get_program_details, search_programs, watch_program), but 'whats_open' breaks the convention (no underscore, abbreviation) and 'save_camp' uses 'camp' while others use 'program', introducing inconsistency.
With 5 tools, the set is well-scoped for a camps and after-school discovery service. Each tool earns its place and covers the core user workflow without being overwhelming or insufficient.
The set covers search, details, saving, alerts, and open availability—core tasks. A minor gap is the lack of a tool to remove from watchlist or cancel alerts, but the main lifecycle is addressed.