export_dataExporte des données électorales vers un fichier téléchargeable (CSV, JSON, TSV).
Deux modes : data (contenu inline) ou source_path (chemin vers fichier existant).
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | ||
| filename | Yes | ||
| file_format | No | csv | |
| source_path | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate idempotentHint=true and destructiveHint=false, and the description aligns by describing a non-destructive export. It adds context about creating a downloadable file and the two modes, which is valuable beyond the annotations. No contradictions.
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?
The description is three lines with essential information front-loaded. Every sentence adds value, no redundancy, and the structure is clear.
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?
Given the tool has 4 parameters and an output schema (not shown), the description covers the core functionality and two modes. It lacks details on handling conflicting parameters or error conditions, but is largely sufficient for basic usage.
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?
Schema description coverage is 0%, but the description partially compensates by explaining that 'data' is inline content and 'source_path' is a file path. However, it does not explain 'filename' or 'file_format', leaving gaps in parameter understanding.
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 clearly states the action (export), resource (électorales), and output formats (CSV, JSON, TSV). It also distinguishes two modes (data and source_path), making the tool's purpose distinct from sibling tools like query_* or visualize.
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 mentions two modes (data vs source_path) but provides no explicit guidance on when to use this tool over alternatives, nor does it specify prerequisites or exclusions. Usage is implied but not clearly differentiated from siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
The query_* tools are mostly cleanly separated by domain (elections, admin, DLP, élus, sociodem), and the output-oriented tools (map, table, visualization, export) are distinct. The main potential confusion is query_sql versus query_elections, since both can access election results, but the descriptions mitigate this by explicitly recommending query_elections for standard analysis.
All tool names follow a consistent lowercase snake_case verb-first convention: query_* for data retrieval, and create_data_table, export_data, generate_map, simulate_fusions, and visualize for actions. There is no mixing of camelCase, inconsistent verb styles, or vague duplicate-like naming.
With 11 tools, the server is well within the ideal scope for a specialized electoral analysis toolset. Each query tool covers a coherent data domain, while mapping, visualization, export, table formatting, and simulation cover distinct workflow needs without redundancy.
The tool surface covers the full electoral analysis workflow: querying results and administrative divisions, socio-demographic profiles, elected officials, municipal candidate data, mapping, custom visualizations, tabular formatting, export, and fusion simulation. The advanced panel actions in query_elections plus the read-only SQL fallback fill most conceivable gaps.