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List years

list_years
Read-onlyIdempotent

Research-item year/decade histogram with dated and undated counts. A date range counts in each spanned bucket. Supports shared item filters and pagination.

Input Schema

NameRequiredDescriptionDefault
toNoLatest year to report (inclusive)
fromNoEarliest year to report (inclusive)
sortNoDefault 'chronological' (oldest first); 'count' ranks by item count
limitNoDefault 200, max 500
bucketNoDefault 'year'
offsetNo
filtersNoResearch-item filters applied before bucketing

Output Schema

NameRequiredDescriptionDefault
sortYes
countYes
bucketYes
offsetYes
resultsYes
has_moreYes
year_rangeNo
dated_itemsYes
next_offsetNo
total_matchesYes
undated_itemsYes
distinct_bucketsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / filters
      Added value: +{
      +  "additionalProperties": false,
      +  "description": "Research-item filters applied before bucketing",
      +  "properties": {
      +    "added_since": {
      +      "maxLength": 40,
      +      "type": "string"
      +    },
      +    "collection": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "contributor": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "country": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "genre": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "has_media": {
      +      "type": "boolean"
      +    },
      +    "keyword": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "language": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "location": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "location_id": {
      +      "exclusiveMinimum": 0,
      +      "maximum": 9007199254740991,
      +      "type": "integer"
      +    },
      +    "modified_since": {
      +      "maxLength": 40,
      +      "type": "string"
      +    },
      +    "project_id": {
      +      "anyOf": [
      +        {
      +          "maxLength": 256,
      +          "type": "string"
      +        },
      +        {
      +          "exclusiveMinimum": 0,
      +          "maximum": 9007199254740991,
      +          "type": "integer"
      +        }
      +      ]
      +    },
      +    "research_section": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "resource_type": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "subject": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "university": {
      +      "maxLength": 1000,
      +      "type": "string"
      +    },
      +    "year_from": {
      +      "maximum": 2200,
      +      "minimum": 0,
      +      "type": "integer"
      +    },
      +    "year_to": {
      +      "maximum": 2200,
      +      "minimum": 0,
      +      "type": "integer"
      +    }
      +  },
      +  "type": "object"
      +}
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "https://json-schema.org/draft/2020-12/schema",
      +  "additionalProperties": {},
      +  "properties": {
      +    "bucket": {
      +      "type": "string"
      +    },
      +    "count": {
      +      "type": "number"
      +    },
      +    "dated_items": {
      +      "type": "number"
      +    },
      +    "distinct_buckets": {
      +      "type": "number"
      +    },
      +    "has_more": {
      +      "type": "boolean"
      +    },
      +    "next_offset": {
      +      "type": "number"
      +    },
      +    "offset": {
      +      "type": "number"
      +    },
      +    "results": {
      +      "items": {
      +        "additionalProperties": false,
      +        "properties": {
      +          "decade": {
      +            "type": "string"
      +          },
      +          "from": {
      +            "type": "number"
      +          },
      +          "item_count": {
      +            "type": "number"
      +          },
      +          "to": {
      +            "type": "number"
      +          },
      +          "year": {
      +            "type": "number"
      +          }
      +        },
      +        "required": [
      +          "item_count"
      +        ],
      +        "type": "object"
      +      },
      +      "type": "array"
      +    },
      +    "sort": {
      +      "type": "string"
      +    },
      +    "total_matches": {
      +      "type": "number"
      +    },
      +    "undated_items": {
      +      "type": "number"
      +    },
      +    "year_range": {
      +      "additionalProperties": false,
      +      "properties": {
      +        "max": {
      +          "type": "number"
      +        },
      +        "min": {
      +          "type": "number"
      +        }
      +      },
      +      "required": [
      +        "min",
      +        "max"
      +      ],
      +      "type": "object"
      +    }
      +  },
      +  "required": [
      +    "count",
      +    "total_matches",
      +    "offset",
      +    "has_more",
      +    "bucket",
      +    "sort",
      +    "distinct_buckets",
      +    "dated_items",
      +    "undated_items",
      +    "results"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower, yet the description adds genuinely non-obvious behavior: a date range contributes to each spanned bucket, and undated items are counted separately. It goes beyond the structured fields, though it doesn't mention the limit cap or truncation 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?

Three short sentences, front-loaded with the tool's purpose and output shape, with zero filler. Each sentence adds a distinct fact (what it returns, the bucketing rule, filter/pagination support).

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?

An output schema exists, so return value details needn't be repeated, and the description covers filters, pagination, and the aggregation rule. It is nearly complete for a 7-param aggregation tool, missing only explicit routing guidance against sibling list/search tools.

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 coverage is high (86%), so the baseline is 3, but the description adds meaning the schema cannot convey: that 'filters' are the shared research-item filter set applied before bucketing, and the bucket-spanning rule that governs how 'from'/'to' interact with 'bucket'. This is useful semantics beyond the per-field descriptions.

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 output artifact — a research-item year/decade histogram with dated and undated counts — which is far more precise than the tool name 'list_years' alone. It does not explicitly contrast itself with sibling aggregation tools like list_publication_facets, so it stops short of full sibling differentiation.

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

Usage Guidelines2/5

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

There is no explicit when-to-use or when-not-to-use guidance and no named alternative (e.g. search_research_items or list_publication_facets) for obtaining date distributions. 'Supports shared item filters and pagination' describes capability, not the condition under which this tool should be chosen over its siblings.

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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