insourcia

search_directors

Read-onlyIdempotent

Recherche de personnes (dirigeants) a travers toutes les entreprises francaises, par nom de famille.

A la difference de search_companies (qui retourne des ENTREPRISES et accepte dirigeant_nom/dirigeant_prenom comme filtres), search_directors retourne directement des PERSONNES avec leur entreprise de rattachement. Cas d'usage : "toutes les entreprises ou siege un dirigeant nomme DUPONT", cartographie d'un reseau de mandats.

Parametres : nom (REQUIS, nom de famille), prenom (optionnel, desambiguise), role (optionnel, ex "President", "Gerant", "Administrateur"). Par defaut seuls les mandats actifs ; include_inactive=true pour inclure les anciens mandats.

Reponse : data[] = personnes { nom, prenom, civilite, role, role_description, date_naissance, annee_naissance, lieu_naissance, type_personne, entreprise { siren, denomination, ville, departement, code_ape } }. pagination { total (nb entreprises matchees), limit, returned }.

DESAMBIGUISATION (important) : un meme nom+prenom recouvre souvent plusieurs personnes distinctes (homonymes). Ne PAS conclure que deux mandats appartiennent a la meme personne sur le seul nom/prenom. Comparer date_naissance (et lieu_naissance) : deux dates differentes = deux personnes distinctes ; date absente = lien NON confirme (ne pas l'affirmer). A l'inverse, ne pas declarer "homonymes" deux mandats partageant la meme date_naissance.

Pour lister TOUTES les entreprises d'une personne donnee une fois sa date de naissance connue, enchainer avec search_director_companies (nom + prenom + date_naissance). Pour la fiche complete d'un dirigeant d'une entreprise donnee, utiliser get_directors avec le SIREN.

Input Schema

TableJSON Schema

Name	Required	Description
`nom`	Yes	Nom de famille du dirigeant recherche (requis).
`role`	No	Role/qualite (optionnel), ex: 'President', 'Gerant', 'Administrateur'.
`limit`	No	Nombre d'entreprises a scanner (defaut 20, max 50).
`prenom`	No	Prenom (optionnel) pour desambiguiser les homonymes.
`context`	Yes	Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): "Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization."
`include_inactive`	No	Inclure les mandats inactifs (defaut: false).

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No
`_user_plan`	No
`pagination`	No
`_quota_remaining_month`	No
`_quota_remaining_today`	No

TDQS

A4.9/5.0

Behavior5/5

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

Annotations already declare readOnlyHint true and destructiveHint false, and the description adds substantial behavioral context: active mandates are returned by default, include_inactive toggles old mandates, and there is an important disambiguation warning about same-name/different-person cases. It also describes the pagination and response structure. No contradiction with annotations.

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 front-loaded with the core purpose, then organized into parameter semantics, response shape, disambiguation notes, and sibling tool routing. Every section carries operational value; nothing feels redundant or decorative.

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

Completeness5/5

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

Given the complexity of disambiguating homonyms and the availability of an output schema, the description is complete: it defines the output structure, explains defaults, warns about identity pitfalls, and gives explicit chaining paths to related tools. There is no missing information that would prevent an agent from using the tool correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds meaning beyond the schema: prenom is described as a disambiguator, role gets example values, and include_inactive's effect on active mandates is explained. It does not deeply expand on limit or context, but the schema already covers them.

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 uses a specific verb and resource: searching for people/directors across all French companies by last name. It explicitly contrasts with search_companies, which returns companies, so the agent can distinguish the tool from siblings without ambiguity. The use case is concrete.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

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

The description gives explicit when-to-use guidance: when you need people rather than companies, e.g. 'all companies where a director named DUPONT sits'. It also identifies when to switch to search_director_companies or get_directors, providing a clear routing rule based on the data already known.

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

A4.3/5.0

Disambiguation4/5

Most tools have clearly distinct resource+action purposes, and the descriptions explicitly contrast near-neighbor tools like search_companies vs resolve_companies and get_events vs search_events. The only real risk is the trio of director-oriented tools, especially search_director_companies vs search_companies with dirigeant filters, which requires careful reading to avoid misselection.

Naming Consistency5/5

All 18 tools follow a consistent snake_case verb_noun pattern: search_, get_, list_, create_, watch_, unwatch_, mark_, resolve_. Singular names are used for single-entity actions and plural for list/search operations, making the pattern predictable. There is no camelCase, vague verb, or style mixing.

Tool Count4/5

18 tools is slightly above the ideal 10-15 range, but the count is justified by the broad domain covering search, company intelligence, watchlists, and news. Each tool appears to earn its place, and there are no obvious stubs or redundant duplicates. It feels a bit heavy but not bloated.

Completeness3/5

The company intelligence surface is very complete: search, deep company data, financials, directors, group graphs, events, and credit risk are all covered. Watchlists also have full add/remove/list coverage, but saved searches have a notable lifecycle gap—create and list exist, yet there is no update, delete, or alert-toggle for existing saved searches, creating a management dead end.

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