get_changesNew FDA clearances and recalls since a date - the monitoring feed. Use for 'what changed this week' questions.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | No | ||
| since | Yes | ISO date, e.g. 2026-08-01 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that this is a monitoring feed returning new items, but does not disclose details like ordering, inclusivity of the date, or default behavior when kind is 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 two short sentences with no filler. It front-loads the core behavior and then gives a direct usage cue, making it easy for an agent to quickly evaluate.
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 read-only monitoring feed, the description plus schema is mostly sufficient for an agent to select and invoke the tool. The lack of an output schema is partially compensated by the clear 'new clearances and recalls' framing, though a bit more detail on default behavior would round it out.
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 50%: 'since' has an ISO date description, while 'kind' only has an enum. The description mentions both clearances and recalls, aligning with the enum, but it does not explain what happens when kind is omitted or how 'since' is interpreted regarding inclusivity.
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 resource ('FDA clearances and recalls') and a clear temporal scope ('since a date'), and labels the tool as 'the monitoring feed.' This distinguishes it from sibling tools like get_clearance and search_recalls, which are for individual or search-based lookups.
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 states when to use the tool: 'Use for "what changed this week" questions.' It does not list exclusions or compare against alternatives, but the intended context is clear.
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 clear primary purpose: AI device list, predicate candidates, monitoring feed, clearance detail, product code stats, recall search, and general full-text search. Minor overlap exists between find_predicates and product_code_stats (both product-code driven) and between search_recalls and search_records, but the descriptions distinguish specialized from general use.
Most tools follow a verb_noun pattern like find_predicates, get_changes, get_clearance, search_recalls, and search_records. Two names — ai_devices and product_code_stats — are noun phrases, creating a minor inconsistency, but the overall pattern remains readable and predictable.
Seven tools is well-scoped for a read-only FDA data server, covering lookup, search, statistics, monitoring, and specialized research use cases without unnecessary duplication. Each tool earns its place.
The set covers clearance details, recall search, product code statistics, change monitoring, predicate research, and the AI device list. There is no dedicated clinical trial tool, though search_records includes trials, and no device classification lookup, but these are workable gaps rather than dead ends.