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Hermes — Air Quality Intelligence

time_patterns

Analyse when pollution is highest — hour of day, day of week, and month.

Returns temporal profiles showing typical patterns. Useful for advising on best times for outdoor exercise, school runs, or commuting.

Args: location: Postcode, place name, or "lat,lon". pollutant: Pollutant to analyse — "NO2", "PM2.5", "PM10", "O3" (default "NO2"). period: Time window — "last_month", "last_3_months", "last_6_months", or "last_year" (default).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNolast_year
locationYes
pollutantNoNO2

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description is the sole source of behavioral information. It discloses that the tool returns 'temporal profiles showing typical patterns' and accepts location/pollutant/period, but it does not elaborate on output structure, data aggregation, or any limitations (e.g., how 'typical' is defined). This is adequate but not rich, warranting a 3.

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 compact and well-structured: a one-sentence summary, a sentence on output, a sentence on use cases, and a neatly formatted Args block. No fluff or redundancy.

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?

While parameters are fully documented, the description is thin on output semantics (no detail on what a 'temporal profile' contains) and does not mention any exclusions or data caveats. Given no output schema, this gap makes it slightly incomplete, so a 3 is warranted.

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?

The schema provides only type and defaults; the description fills in all semantic details: location format ('Postcode, place name, or "lat,lon"'), valid pollutant values, and valid period values. This fully compensates for the 0% schema coverage, so a 5 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 opens with 'Analyse when pollution is highest — hour of day, day of week, and month', which clearly identifies the tool's function (temporal analysis) and distinguishes it from siblings like trend_analysis or chart_aq_trend by specifying the exact time granularities. It also states the output ('temporal profiles'), making the 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 Guidelines4/5

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

The phrase 'Useful for advising on best times for outdoor exercise, school runs, or commuting' provides concrete application contexts, but it does not explicitly contrast with alternative tools or state when not to use it. This is clear context without exclusions, aligning with a score of 4.

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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