insourcia

get_credit_risk

Read-onlyIdempotent

Score de risque credit d'UNE entreprise francaise (par SIREN).

Retourne le grade de risque (AAA -> D), la probabilite de defaut a 3/6/12 mois (taux du grade, master-scale) et les 5 facteurs principaux (aggravants / attenuants).

Reserve au plan Pro. Reponses possibles :

entreprise scoree : { scorable:true, risk:{ grade, grade_default_rate, factors, as_of, model } }
entreprise non scoree (pas de comptes recents) : { scorable:false, risk:null }
SIREN inconnu : erreur 404.

Utiliser pour une entreprise a la fois (use case risque fournisseur / due diligence).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`siren`	Yes	SIREN a 9 chiffres
`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."

Output Schema

TableJSON Schema

Name	Required	Description	Default
`risk`	Yes
`siren`	Yes
`reason`	No
`scorable`	Yes

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare this as read-only and idempotent. The description adds meaningful behavioral context: possible response variants (scorable vs non-scorable), 404 for unknown SIREN, and restriction to Pro plan, which are not present in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is well-organized with a clear front-loaded purpose, followed by return values, plan restriction, response shapes, and usage hint. Each sentence carries relevant information, though the response-shape list makes it slightly longer than strictly necessary.

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 two-parameter read-only tool with an output schema, the description covers the important operational cases: success, non-scorable company, and 404 error. It also notes the plan restriction and use cases, leaving little ambiguity for an agent.

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

Parameters3/5

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

Schema coverage is 100%: both siren and context have full descriptions. The tool description only reinforces 'one company at a time' without adding new parameter-level detail, so the baseline of 3 applies.

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 states the tool scores the credit risk of one French company by SIREN and lists specific returned outputs (risk grade, default probabilities, factors). This distinguishes it from sibling tools like get_company and get_financials.

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 explicitly says the tool is for one company at a time and names the target use cases: supplier risk and due diligence. It does not mention exclusions or compare itself to alternatives, but the context is clear.

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.

Resources

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