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identify_plant_from_photo

Identify a plant species from a photo using Pl@ntNet. Provide an image path and optional plant organ to get top candidates with confidence scores.

Instructions

Identify a plant species from a local photo using Pl@ntNet.

image_path may be absolute or a file name inside the workspace folder. organ describes what the photo shows: auto, leaf, flower, fruit, bark, habit or other. Returns the top candidates with a confidence score each -- always report the confidence, and treat anything below ~30% as a guess.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
organNoauto
image_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that it returns top candidates with confidence scores, instructs to always report confidence, and flags a ~30% threshold for guesses. It also explains the organ parameter's meaning. It does not cover error conditions or rate limits, but for a simple identification tool this is adequate.

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

Conciseness5/5

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

The description is three sentences with zero redundancy. The main purpose is front-loaded, followed by essential parameter details and a critical behavioral note. Every sentence earns its place.

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

Completeness4/5

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

For a simple tool with two parameters, the description covers the core purpose, parameter formats, and output behavior (confidence scores). It mentions the output schema exists, so return-value details are not required. It does not address failure modes, but that is a minor omission given the tool's simplicity.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It explains image_path may be absolute or a workspace-relative file name, and enumerates organ values (auto, leaf, flower, fruit, bark, habit, other). This adds substantial meaning beyond the bare schema titles, fully compensating for the coverage gap.

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

Purpose5/5

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

The description states a specific verb and resource: 'Identify a plant species from a local photo using Pl@ntNet.' It clearly distinguishes the tool from its siblings (classify_species_in_country, get_management_recommendations, list_country_alien_species) which address different tasks, so an agent can select it without ambiguity.

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 description provides clear context: it handles local photos and uses Pl@ntNet, implying it should be used when a user supplies a photo to identify. It does not explicitly name alternatives or exclusions, but the sibling tools make the domain clear. This meets the 'clear context, no exclusions' bar.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.