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Atlarium Habitat Database MCP

Check species compatibility

check_species_compatibility
Read-onlyIdempotent

Check basic compatibility information between habitat species using Atlarium data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ghNoWater hardness, conductivity or TDS-style value for advisory matching.
khNoWater hardness, conductivity or TDS-style value for advisory matching.
phNoWater pH value on the 0 to 14 scale.
speciesYesList of species names or slugs to compare, from 1 to 20 entries.
languageNoOptional preferred response language: it, en or es.
tank_litersNoTank or habitat volume in liters.
temperatureNoWater or ambient temperature in degrees Celsius.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
toolYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • removedOutput schema / properties / generated_at
      Removed value: -{
      -  "type": "string"
      -}
    • changedOutput schema / required
      Previous value: -[
      -  "data",
      -  "generated_at",
      -  "tool"
      -]New value: +[
      +  "data",
      +  "tool"
      +]
  2. Changed8 schema fields changed
    • addedInput schema / properties / gh / description
      Added value: +"Water hardness, conductivity or TDS-style value for advisory matching."
    • addedInput schema / properties / kh / description
      Added value: +"Water hardness, conductivity or TDS-style value for advisory matching."
    • addedInput schema / properties / language / description
      Added value: +"Optional preferred response language: it, en or es."
    • addedInput schema / properties / ph / description
      Added value: +"Water pH value on the 0 to 14 scale."
    • addedInput schema / properties / species / description
      Added value: +"List of species names or slugs to compare, from 1 to 20 entries."
    • addedInput schema / properties / species / items / description
      Added value: +"Species common name, scientific name or slug to evaluate."
    • addedInput schema / properties / tank_liters / description
      Added value: +"Tank or habitat volume in liters."
    • addedInput schema / properties / temperature / description
      Added value: +"Water or ambient temperature in degrees Celsius."
  3. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": false,
      +  "properties": {
      +    "data": {},
      +    "generated_at": {
      +      "type": "string"
      +    },
      +    "tool": {
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "data",
      +    "generated_at",
      +    "tool"
      +  ],
      +  "type": "object"
      +}
  4. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description only needs to add context beyond these. It adds 'basic' and 'using Atlarium data', which qualifies scope and data source, but does not elaborate on what 'basic' means or any response behavior.

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 a single, front-loaded sentence with no filler. It concisely states the action, object, and data source without wasting words.

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?

The tool has seven parameters and an output schema, and annotations cover safety. The description is adequate but minimal; it doesn't explain how to choose this over sibling tools and the term 'basic compatibility' is vague. However, the output schema likely covers return value details, so this is not a critical gap.

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

Parameters3/5

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

Schema description coverage is 100%, with all seven parameters individually described in the input schema. The tool description itself adds no additional parameter semantics, but per the rubric baseline 3 is appropriate when the schema already does the heavy lifting.

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 uses the verb 'Check' and specifies the resource 'compatibility information between habitat species', along with the data source 'Atlarium data'. This clearly distinguishes it from sibling tools like get_fish_profile or suggest_species_for_tank, though it does not explicitly contrast them.

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

Usage Guidelines3/5

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

The description implies a use case—checking compatibility between species—but provides no explicit when-to-use guidance, alternatives, or exclusions. Given the large sibling set that includes related tools like suggest_species_for_tank, the lack of usage context leaves some ambiguity.

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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