get_stats
Get the number of published peptide providers, places and categories, and when the data last changed.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get the number of published peptide providers, places and categories, and when the data last changed.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds genuinely new behavioral context beyond them: the counts are scoped to *published* providers only, and the response includes a data-freshness signal ('when the data last changed'). It does not describe response shape, but that gap is minor against the annotation coverage.
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?
A single sentence that front-loads the primary deliverable (the counts) and appends the secondary one (last-changed). Every clause carries information; nothing is repeated or padded.
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?
With no input parameters, no output schema, and annotations covering safety, the description's job is mainly to convey what comes back — and it does state the counted entities and the freshness field. It could be marginally stronger by sketching the return shape, but an agent has enough to call it 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 tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline for a parameterless tool is 4, and no schema/description conflict exists.
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?
States a specific verb ('get the number of') and concrete resources (published peptide providers, places, categories), plus an extra deliverable (last-changed timestamp). This clearly separates it from the list_*/search_* siblings, which return items rather than aggregate counts. It stops short of naming an alternative, so it's clear but not maximally differentiated.
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?
There is no explicit when-to-use or when-not-to-use statement and no sibling is named. However, the count-only framing strongly implies the intended use case (a quick aggregate overview rather than item retrieval), which fits the 'implied usage' bar.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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