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Africa Multiple collection overview

get_collection_overview
Read-onlyIdempotent

Start here: corpus counts, text coverage, breakdowns, dates, snapshot freshness and refresh status.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
countsYes
refreshYes
site_urlYes
universitiesNo
data_snapshotYes
collection_nameYes
items_by_languageNo
metadata_exposureNo
research_sectionsNo
content_date_rangeYes
items_by_universityNo
items_by_resource_typeYes
items_by_research_sectionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "https://json-schema.org/draft/2020-12/schema",
      +  "additionalProperties": false,
      +  "properties": {
      +    "collection_name": {
      +      "type": "string"
      +    },
      +    "content_date_range": {
      +      "anyOf": [
      +        {
      +          "additionalProperties": false,
      +          "properties": {
      +            "earliest": {
      +              "type": "number"
      +            },
      +            "latest": {
      +              "type": [
      +                "number",
      +                "null"
      +              ]
      +            }
      +          },
      +          "required": [
      +            "earliest",
      +            "latest"
      +          ],
      +          "type": "object"
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ]
      +    },
      +    "counts": {
      +      "additionalProperties": {
      +        "type": "number"
      +      },
      +      "propertyNames": {
      +        "type": "string"
      +      },
      +      "type": "object"
      +    },
      +    "data_snapshot": {
      +      "additionalProperties": false,
      +      "properties": {
      +        "api_base": {
      +          "type": "string"
      +        },
      +        "fetched_at": {
      +          "type": "string"
      +        },
      +        "max_modified": {
      +          "type": [
      +            "string",
      +            "null"
      +          ]
      +        },
      +        "note": {
      +          "type": "string"
      +        },
      +        "source": {
      +          "type": "string"
      +        }
      +      },
      +      "required": [
      +        "source",
      +        "fetched_at",
      +        "max_modified",
      +        "api_base",
      +        "note"
      +      ],
      +      "type": "object"
      +    },
      +    "items_by_language": {
      +      "additionalProperties": {
      +        "type": "number"
      +      },
      +      "propertyNames": {
      +        "type": "string"
      +      },
      +      "type": "object"
      +    },
      +    "items_by_research_section": {
      +      "additionalProperties": {
      +        "type": "number"
      +      },
      +      "propertyNames": {
      +        "type": "string"
      +      },
      +      "type": "object"
      +    },
      +    "items_by_resource_type": {
      +      "additionalProperties": {
      +        "type": "number"
      +      },
      +      "propertyNames": {
      +        "type": "string"
      +      },
      +      "type": "object"
      +    },
      +    "items_by_university": {
      +      "additionalProperties": {
      +        "type": "number"
      +      },
      +      "propertyNames": {
      +        "type": "string"
      +      },
      +      "type": "object"
      +    },
      +    "metadata_exposure": {
      +      "type": "string"
      +    },
      +    "refresh": {
      +      "additionalProperties": false,
      +      "properties": {
      +        "enabled": {
      +          "type": "boolean"
      +        },
      +        "error_class": {
      +          "type": [
      +            "string",
      +            "null"
      +          ]
      +        },
      +        "in_flight": {
      +          "type": "boolean"
      +        },
      +        "last_attempt": {
      +          "type": [
      +            "string",
      +            "null"
      +          ]
      +        },
      +        "last_success": {
      +          "type": [
      +            "string",
      +            "null"
      +          ]
      +        }
      +      },
      +      "required": [
      +        "enabled",
      +        "in_flight",
      +        "last_attempt",
      +        "last_success",
      +        "error_class"
      +      ],
      +      "type": "object"
      +    },
      +    "research_sections": {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    "site_url": {
      +      "type": "string"
      +    },
      +    "universities": {
      +      "additionalProperties": {
      +        "type": "string"
      +      },
      +      "propertyNames": {
      +        "type": "string"
      +      },
      +      "type": "object"
      +    }
      +  },
      +  "required": [
      +    "collection_name",
      +    "site_url",
      +    "counts",
      +    "items_by_resource_type",
      +    "content_date_range",
      +    "data_snapshot",
      +    "refresh"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and closed-world, so the safety profile is fully covered. The description adds the fact that it reports snapshot freshness and refresh status, which is mildly useful context, but does not mention auth, rate limits, or cost beyond that.

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?

A single front-loaded sentence ('Start here: ...') with no filler; each listed item earns its place by signalling returned content. It is a fragment rather than a full sentence, but it is efficient.

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 zero-parameter, read-only tool with an output schema that already documents the return shape, the description is nearly complete. It could do more to differentiate from sibling aggregate tools, but nothing essential for correct invocation is missing.

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?

The tool takes zero parameters, so the baseline is 4. There is nothing for the description to disambiguate at the parameter level.

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 concrete outputs (corpus counts, text coverage, breakdowns, dates, snapshot freshness, refresh status), so an agent understands this is an aggregate overview of a collection. It does not, however, distinguish itself from siblings like get_data_quality or list_collections, which also report collection-level statistics.

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?

'Start here' implies the tool should be used first, giving implicit usage guidance. But no explicit when-to-use/when-not conditions are stated and no alternative (e.g. get_data_quality) is named for the cases where a different tool is appropriate.

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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