yellide

New species described from India

new_species

Read-only

Species described from India since a year (2007 or later), from Plazi, the BSI Plant Discoveries and the ZSI Animal Discoveries: the year, the group, the state of the type locality, the journal and a link to the paper, and whether it has been recorded since. "new species discovered in India 2025", "new frog species from India".

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "since": "<since>"
    },
    "name": "new_species"
  }
}

Input Schema

Name	Required	Description
`group`	No	A group of the list, or a word of it: "Birds", "butterflies", "mammals" (all mammal groups), "orchids". See yellide://groups.
`limit`	No	Rows per page, 1 to 100 (default 50).
`since`	Yes	Described in this year or later (2007 or later).
`state`	No	The state of the type locality.
`cursor`	No	next_cursor from the previous page.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 12, 2026

TDQS

A3.7/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=false, matching the curated-database nature of the tool. The description adds useful provenance (which three data sources feed it) and enumerates the returned fields, but says nothing about pagination behavior or result ordering, which matters for a paged list tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The lead sentence is front-loaded with the scope and the source set, then the returned fields, then example queries. The phrasing "since a year (2007 or later)" is slightly awkward and redundant with the schema, but overall there is little waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Because there is no output schema, the description does the right thing by enumerating returned fields and data provenance. However, for a five-parameter paged query tool it omits how results are ordered and how cursor pagination terminates, leaving the agent to discover that from the schema alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3, and the description adds real meaning by tying the filters to the dataset: the year bound (2007 or later) and the notion that the state filter refers to the type locality. The group parameter's fuzzy matching is left to the schema and the yellide://groups reference.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific resource and scope: species described from India since 2007, sourced from Plazi, BSI Plant Discoveries and ZSI Animal Discoveries. It is clear what the tool returns (year, group, state, journal, paper link, recorded-since flag), but it never contrasts itself with siblings such as list_species or find_species, so differentiation is left to inference.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The quoted example queries ("new species discovered in India 2025", "new frog species from India") give concrete natural-language triggers that map cleanly onto this tool. There is no explicit when-not guidance or pointer to sibling tools for related tasks.

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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