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lpicci96

unesco-mcp

by lpicci96

count_indicators

Count UNESCO UIS indicators matching precise filter criteria, including theme, disaggregation, year coverage, and update date. Returns the exact count and a summary of filters applied.

Instructions

Count UNESCO UIS indicators matching precise filter criteria.

Use this tool when the user wants to know how many indicators exist for a given combination of filters, including year coverage or update date constraints. Unlike search_indicators, this tool returns an exact count and accepts year range filters.

All provided filters are combined with AND logic. If no filters are provided, returns the total count of all indicators in the database.

Args: theme: Exact theme code (from list_themes). disaggregation_types: List of disaggregation type codes. Indicators must support ALL listed types. disaggregation_values: List of disaggregation value codes. Indicators must match ALL listed values. coverage_start_year: Only count indicators whose data begins by this year (i.e. timeLine_min <= year). coverage_end_year: Only count indicators whose data extends through this year (i.e. timeLine_max >= year). updated_since: ISO date string (e.g. "2024-01-01"). Only count indicators updated on or after this date.

Returns: A dictionary with: - "count": The exact number of indicators matching all provided filters. - "filters_applied": A summary of which filters were used.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
themeNo
disaggregation_typesNo
disaggregation_valuesNo
coverage_start_yearNo
coverage_end_yearNo
updated_sinceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

While the tool is likely read-only, the description does not explicitly state safety, authentication needs, or side effects. It does explain filtering logic and return format, but with no annotations, the description should disclose behavioral traits beyond the obvious. A score of 3 reflects adequate but incomplete transparency.

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 concise, well-structured with a summary line, usage guidelines, logic note, Args block, and Returns block. Every sentence adds value, no redundancy, and the layout aids readability.

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

Completeness5/5

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

Given the tool's simplicity (count with filters), the description covers all necessary context: purpose, usage, parameters with detailed semantics, AND logic, behavior with no filters, and return format (output schema). No obvious gaps remain.

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%, but the description provides detailed Args section with exact meaning, examples, and logic (e.g., 'timeLine_min <= year'). This fully compensates for the lack of schema descriptions, adding significant value beyond the input schema.

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 uses a specific verb 'Count' and resource 'UNESCO UIS indicators', clearly distinguishing from sibling tool 'search_indicators' which returns list. It explicitly states this tool returns an exact count and accepts year range filters, making purpose unambiguous.

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

Usage Guidelines5/5

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

The description explicitly states 'Use this tool when the user wants to know how many indicators exist for a given combination of filters...' and contrasts with 'search_indicators', providing clear when-to-use and alternative. Also explains AND logic and behavior with no filters.

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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