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André — Analyse électorale française

by vote.andre

Profil social des candidats municipaux

query_dlp
Read-onlyIdempotent

Requête les données DLP (composition sociale des candidats municipaux 2020).

    ~546 000 candidats dans ~10 000 communes (≥1 000 hab.).
    Classes : CDOM (dominant), CMOY (moyen), CSUB (subalterne), RET (retraité), AUTRES.
    Actions : summary, composition, parite, listes, candidats, professions, sortants.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sexeNo
actionYes
classeNo
searchNo
tetes_onlyNo
commune_codeNo
sortants_onlyNo
departement_codeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

B3.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint. The description adds valuable context about the data scale (~546k candidates, ~10k communes) and the classification scheme, beyond what annotations provide. 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively short but uses a bullet-like list for actions and classes. It front-loads the main query purpose but could be more structured and include parameter explanations without getting too long.

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

Completeness2/5

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

Given 8 parameters, 0% schema coverage, and no parameter descriptions, the tool definition is incomplete. The output schema exists but is not shown. The description provides a high-level overview but lacks details needed to use the tool correctly without guessing parameter values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. The description only mentions 'actions' and 'classe' briefly, ignoring 6 other parameters (e.g., sexe, search, tetes_only). It fails to compensate for the lack of schema documentation.

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 clearly identifies the tool as querying DLP data (social composition of 2020 municipal candidates), listing specific classes and actions. This distinctively separates it from sibling tools like query_elections or query_sociodem.

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?

It lists possible actions (summary, composition, etc.) and classes, implying usage contexts, but does not provide explicit guidance on when to use this tool versus alternatives or when not to use 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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TDQS

A3.7/5.0
Disambiguation4/5

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.

Naming Consistency5/5

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.

Tool Count5/5

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.

Completeness5/5

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.

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