list_recent_analysesListe les analyses (articles) les plus récentes de l0g.fr, de la plus récente à la plus ancienne, avec titre, URL, date, description et thèmes.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Nombre d'analyses à renvoyer. | |
| language | No | Langue optionnelle : fr ou en. Sans filtre, liste bilingue. |
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | ||
| error | No | ||
| analyses | No |
Changes observed during successful MCP inspections.
Input schema / properties / languageAdded value: +{
+ "description": "Langue optionnelle : fr ou en. Sans filtre, liste bilingue.",
+ "enum": [
+ "fr",
+ "en"
+ ],
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool read-only and non-destructive. The description adds behavioral context by disclosing the sort order, the source site, and the response fields. It does not contradict annotations and provides useful detail beyond the safety hints, while the output schema covers the remaining return structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence contains the action, scope, ordering, and returned fields with no filler or repetition. Every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list operation with two optional parameters and an output schema, the description plus annotations and schema provide everything needed: source, ordering, returned fields, parameter defaults, and enum values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both limit and language, including defaults, constraints, and enum values. The description does not add extra parameter semantics, but the schema already carries the burden fully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource ('Liste les analyses les plus récentes de l0g.fr'), specifies the ordering ('de la plus récente à la plus ancienne'), and enumerates the returned fields (titre, URL, date, description, thèmes). This clearly distinguishes it from siblings like get_article and search_content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: it is the tool for listing recent analyses from l0g.fr in reverse chronological order. It does not explicitly name alternatives or when-not-to-use cases, but the scope is precise enough that an agent can infer when to select it.
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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