insourcia

list_watched_companies

Read-onlyIdempotent

Liste des societes surveillees par l'utilisateur dans ses listes de veille (page /lists de l'app Insourcia).

Utiliser cet outil :

AVANT watch_company, pour verifier si une societe est deja surveillee et connaitre les listes existantes (leur nom exact).
Pour repondre a "quelles societes je surveille ?" / "qu'y a-t-il dans ma liste X ?".

list_name (optionnel) restreint a une liste precise (nom exact). Sans list_name, toutes les listes de l'utilisateur sont retournees. Un list_name qui ne matche aucune liste renvoie companies: [] et total: 0 (ce n'est pas une erreur : simplement aucune societe surveillee sous ce nom).

Reponse : { companies: [{ siren, company_name, naf_code, region, list_id, list_name, added_at }] (aplaties toutes listes confondues, plus recentes d'abord), lists: [{ id, name, company_count, alert_enabled }], total, url (page /lists) }.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`list_name`	No	Nom exact de la liste a consulter. Ex: "Surveillance", "Cibles M&A". Omis = toutes les listes.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`url`	Yes
`lists`	Yes
`total`	Yes
`companies`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedSep 3, 2026

addedInput schema / additionalProperties
```
Added value: +false
```

removedInput schema / properties / context

Removed value: -{
-  "description": "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.\"",
-  "type": "string"
-}

removedInput schema / required
```
Removed value: -[
-  "context"
-]
```

Changed3 schema fields changedSep 1, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

addedInput schema / properties / context

Added value: +{
+  "description": "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.\"",
+  "type": "string"
+}

addedInput schema / required
```
Added value: +[
+  "context"
+]
```

First observedSep 1, 2026

TDQS

A4.6/5.0

Behavior5/5

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

The description goes well beyond the readOnlyHint and destructiveHint annotations. It explains that a non-matching list_name returns companies: [] and total: 0 rather than an error, that omitting list_name returns all lists, that results are flattened and sorted newest first, and it details the response fields. This is rich behavioral context.

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-structured with a clear purpose, bulleted usage cases, parameter behavior, and a response format section. It is somewhat detailed but every section carries useful information; no fluff or redundancy beyond a minor overlap with the schema's list_name description.

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?

The description covers all essential context: purpose, usage timing, optional parameter behavior, invalid-input behavior, response structure, ordering, and even the relevant app page. Nothing an agent needs to call this tool correctly 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 coverage is 100%, so the schema already documents list_name. The description adds meaningful edge-case behavior: an unmatched list_name is not an error, and omission means all lists. This exceeds the baseline but is not needed for basic parameter understanding.

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 states a specific verb and resource: 'Liste des societes surveillees par l'utilisateur dans ses listes de veille'. It also ties the tool to a concrete app page (/lists) and gives example user questions, making the tool's purpose immediately clear and distinct from siblings like list_saved_searches.

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?

The description clearly says when to use the tool: before watch_company, and to answer questions about watched companies or list contents. It does not explicitly mention when not to use it or compare it to list_saved_searches, but the usage context is strong enough to guide selection.

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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