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Je croise circonstance et météo

recommend_weather_look
Read-onlyIdempotent

Je croise la circonstance et le bulletin, ou je dis si la pièce tient. Passe question=. Jamais Paris par défaut. La ville n'est pas stockée.

Input Schema

NameRequiredDescriptionDefault
atNoISO 8601 or natural French time.
cityNoAutre nom de location.
pieceNoPièce de vêtement, ex. jupe-cuir, pantalon-cuir, robe-cuir, chemisier.
latitudeNoLatitude, -90 to 90. Requires longitude.
locationNoVille ou lieu pour la météo, ex. Paris, Rodez. Vide = demander la ville.
occasionNoOccasion ou contexte, ex. bureau, dîner, mariage invitée, week-end. Vide = libre.
questionNoQuestion de style en langage naturel, ex. « Quelle veste avec une jupe en cuir bordeaux au bureau ? »
longitudeNoLongitude, -180 to 180. Requires latitude.
transportNoMoyen de déplacement : marche, vélo, transports, voiture. Sert à adapter chaussures et longueurs.
outdoor_minutesNoMinutes outside, 0 to 180.

Output Schema

NameRequiredDescriptionDefault
errorNo
imageNo
actionNo
limitsNo
reasonNo
sourceNo
messageNo
privacyNo
successYes
weatherNo
locationNo
timezoneNo
suggestionsNo
circumstanceNo
location_labelNo
recommendationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changed
    • addedInput schema / properties / location / description
      Added value: +"Ville ou lieu pour la météo, ex. Paris, Rodez. Vide = demander la ville."
    • addedInput schema / properties / occasion / description
      Added value: +"Occasion ou contexte, ex. bureau, dîner, mariage invitée, week-end. Vide = libre."
    • addedInput schema / properties / piece / description
      Added value: +"Pièce de vêtement, ex. jupe-cuir, pantalon-cuir, robe-cuir, chemisier."
    • addedInput schema / properties / question / description
      Added value: +"Question de style en langage naturel, ex. « Quelle veste avec une jupe en cuir bordeaux au bureau ? »"
    • addedInput schema / properties / transport / description
      Added value: +"Moyen de déplacement : marche, vélo, transports, voiture. Sert à adapter chaussures et longueurs."
  2. First observed

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld). The description adds genuine behavioral context beyond them: the city is not persisted between calls and no default location is assumed. It does not say whether weather is fetched remotely, how failures on unknown cities behave, or what form the verdict takes.

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?

Extremely short and front-loaded: purpose first, then the location constraints. Every clause carries information, but 'Passe question=' is cryptic to the point of costing more in decoding time than it saves in length.

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?

With an output schema, rich annotations, and fully described parameters, the minimum for correct invocation is met. Still, for a 10-parameter tool that sits beside recommend_look and weather_looks, the description omits how it differs from them and how the many optional inputs interact, leaving routing ambiguous.

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 description coverage is 100% across 10 parameters, so the baseline is 3. The description's mention of 'question=' and 'la ville' only gestures at two of the parameters and adds no syntax or precedence rules (e.g. when piece+occasion should be used instead of a free-text question).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description says it cross-references the occasion ('la circonstance') and the weather bulletin, and can judge whether a garment works — so the gist is a weather-aware outfit recommendation. But the phrasing is telegraphic and it never distinguishes itself from the sibling recommend_look or weather_looks, which an agent could easily confuse it with.

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?

'Jamais Paris par défaut' and 'La ville n'est pas stockée' give concrete usage constraints: the agent must supply a location explicitly each call and must not assume a default. However, there is no guidance on when to pick this over recommend_look, weather_looks, or get_weather_context — the largest gap given 21 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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