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Nearby Observations

nearby_observations
Read-onlyIdempotent

Recent BIRD sightings within a radius of a given latitude/longitude — eBird is a birds-only database and needs numeric lat/lon coordinates (not a place name). Useful for "what birds are around this location right now."

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
backNoDays back (1-30, default 14)
dist_kmNoRadius in km (1-50, default 25)
latitudeYesLatitude
longitudeYesLongitude
max_resultsNo1-10000 (default 100)
species_codeNoOptional species filter

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of observations returned
centerYesCenter point of search radius
observationsYesList of nearby bird observations

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "latitude": 37.7749,
      +    "longitude": -122.4194
      +  },
      +  {
      +    "back": 7,
      +    "dist_km": 10,
      +    "latitude": 40.7128,
      +    "longitude": -74.006,
      +    "species_code": "amegfi"
      +  }
      +]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "center": {
      +      "description": "Center point of search radius",
      +      "properties": {
      +        "latitude": {
      +          "description": "Center latitude",
      +          "type": "number"
      +        },
      +        "longitude": {
      +          "description": "Center longitude",
      +          "type": "number"
      +        }
      +      },
      +      "required": [
      +        "latitude",
      +        "longitude"
      +      ],
      +      "type": "object"
      +    },
      +    "count": {
      +      "description": "Number of observations returned",
      +      "type": "number"
      +    },
      +    "observations": {
      +      "description": "List of nearby bird observations",
      +      "items": {
      +        "properties": {
      +          "checklist_id": {
      +            "description": "eBird checklist submission ID",
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "common_name": {
      +            "description": "Common name of the species",
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "count": {
      +            "description": "Number of birds observed",
      +            "type": [
      +              "number",
      +              "null"
      +            ]
      +          },
      +          "exotic_category": {
      +            "description": "Exotic status category if applicable",
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "latitude": {
      +            "description": "Latitude of observation",
      +            "type": [
      +              "number",
      +              "null"
      +            ]
      +          },
      +          "location": {
      +            "description": "Location name",
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "location_id": {
      +            "description": "eBird location identifier",
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "longitude": {
      +            "description": "Longitude of observation",
      +            "type": [
      +              "number",
      +              "null"
      +            ]
      +          },
      +          "observed_at": {
      +            "description": "ISO datetime of observation",
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "private_location": {
      +            "description": "Whether location is private",
      +            "type": [
      +              "boolean",
      +              "null"
      +            ]
      +          },
      +          "reviewed": {
      +            "description": "Whether observation was reviewed",
      +            "type": [
      +              "boolean",
      +              "null"
      +            ]
      +          },
      +          "scientific_name": {
      +            "description": "Scientific name of the species",
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "species_code": {
      +            "description": "eBird species code",
      +            "type": [
      +              "string",
      +              "null"
      +            ]
      +          },
      +          "valid": {
      +            "description": "Whether observation passed validation",
      +            "type": [
      +              "boolean",
      +              "null"
      +            ]
      +          }
      +        },
      +        "required": [],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    }
      +  },
      +  "required": [
      +    "center",
      +    "count",
      +    "observations"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already cover safety traits (readOnly, openWorld, idempotent, not destructive). The description adds no additional behavioral details beyond input format constraints, which is adequate but not exceptional.

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?

Two sentences: first states core function and constraint, second provides usage context. No wasted words, front-loaded with essential info.

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?

With an output schema present and moderate complexity (6 params), the description covers purpose and key constraint. It omits mention of optional parameters, but schema covers them. Adequately complete for a read-only query tool.

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 coverage is 100% and descriptions are already present for all 6 parameters. The description does not add extra meaning beyond what the schema provides, so baseline 3 is appropriate.

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 clearly states it retrieves recent bird sightings within a radius of lat/lon. It specifies 'BIRD sightings' and notes eBird is birds-only, distinguishing it from other observation tools.

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 gives a clear use case ('what birds are around this location right now') and implies the need for numeric coordinates. It does not explicitly state when not to use or list alternatives, but the context is strong.

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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