insourcia

search_events

Read-onlyIdempotent

Recherche unifiee d'evenements d'entreprise (cross-SIREN), basee sur notre index ES.

Renvoie des EVENEMENTS individuels (pas des entreprises) : { date, type, siren, denomination, data }. Couvre 8 types : cession (cessions de fonds), procedure (procedures collectives), depot_comptes, augmentation_capital, marche_public, subvention, radiation, creation.

Couvre les evenements BODACC (cessions, procedures collectives, radiations, creations) ainsi que les depots de comptes, augmentations de capital, marches publics et subventions derives des scalaires silver.

REGLE : preciser au moins un filtre region / departement / code_naf, OU un filtre d'evenement (date_min, date_max, cedant_siren, cessionnaire_siren, prix_min/max, tribunal, procedure_type) — sinon 400.

Cas d'usage :

"Cessions de fonds > 1M en Ile-de-France depuis 2024" → type="cession", region="Ile-de-France", date_min="2024-01-01", prix_min=1000000
"Procedures collectives a Lyon" → type="procedure", departement="69"
"Marches publics recents dans le BTP" → type="marche_public", code_naf="4120A"

Input Schema

TableJSON Schema

Name	Required	Description
`type`	No	Types d'evenements (CSV) : cession, procedure, depot_comptes, augmentation_capital, marche_public, subvention, radiation, creation. Defaut : tous.
`limit`	No	Nombre d'evenements (defaut 50, max 200)
`cursor`	No	Curseur de pagination (plan Pro uniquement)
`region`	No	Region. Ex: "Ile-de-France", "Bretagne"
`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."
`code_naf`	No	Code NAF/APE (CSV possible)
`date_max`	No	Date max (YYYY-MM-DD)
`date_min`	No	Date min (YYYY-MM-DD)
`prix_max`	No	Prix de vente max en euros (filtre cession)
`prix_min`	No	Prix de vente min en euros (filtre cession)
`tribunal`	No	Tribunal (filtre procedure, recherche partielle)
`departement`	No	Code departement. Ex: "75", "69"
`cedant_siren`	No	SIREN du cedant (filtre cession)
`procedure_type`	No	Type(s) de procedure (CSV) : liquidation, redressement, sauvegarde, conciliation
`cessionnaire_siren`	No	SIREN du cessionnaire (filtre cession)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	Yes
`pagination`	Yes

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already convey read-only, idempotent, non-destructive, open-world behavior. The description adds useful behavioral context: event-level results, coverage of BODACC and silver scalar sources, and the mandatory-filter condition. 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 presents the coverage, the critical filter rule, and compact examples. Every sentence earns its place for a tool with 15 parameters.

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?

For a complex search tool with 15 parameters and rich schema/annotations, the description covers output shape, event type coverage, data sources, the mandatory-filter rule, and representative use cases. The output schema handles return-value details, so nothing essential is missing.

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 description coverage is 100%, so the baseline is 3. The description adds value by mapping natural-language use cases to specific parameters (e.g., 'Cessions de fonds > 1M en Ile-de-France depuis 2024' -> type, region, date_min, prix_min) and clarifying filter semantics across event types.

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

Purpose4/5

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

The description clearly states a specific verb and resource: a unified cross-SIREN search that returns individual events (not companies), and enumerates the eight event types. It does not explicitly differentiate from the sibling get_events, so it falls short of a 5.

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

Usage Guidelines4/5

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

It gives an explicit filter requirement rule (region/department/NAF or event filter, else 400) and three concrete query-to-parameter examples. It does not name alternatives or state when not to use this tool, so it stops short of full exclusion guidance.

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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