insourcia

list_saved_searches

Read-onlyIdempotent

Liste des recherches sauvegardees de l'utilisateur (page /news - Veille de l'app Insourcia).

Utiliser cet outil :

AVANT create_saved_search, pour verifier qu'une veille equivalente n'existe pas deja et eviter les doublons de nom.
Pour repondre a "quelles veilles ai-je ?" / "quelles sont mes recherches sauvegardees ?".

Reponse : { saved_searches: [{ id, name, filters (filtres normalises stockes), result_count (nombre de societes matchant, null si indisponible), alert_enabled (alerte quotidienne nouvelles societes active ou non), url (page /news), created_at }], total }. Les recherches sont triees de la plus recente a la plus ancienne. Liste vide = aucune veille configuree.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Nombre max de recherches retournees (defaut 100)
`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
`total`	Yes
`saved_searches`	Yes

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context beyond that: results are sorted newest-to-oldest, an empty list means no saved searches exist, result_count can be null, and alert_enabled is explained. This helps the agent interpret the response correctly.

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 well-structured: a one-line purpose, a clear bulleted usage section, and a compact response definition. Every section earns its place and is scannable for an agent.

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 simple read-only list tool with full parameter schema coverage and an output schema, the description covers use cases, sorting, null semantics, and empty-list meaning. No critical information an agent needs to call or interpret this tool is missing.

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 description coverage is 100%, so the schema already documents both limit and context. The description adds no extra parameter-level meaning, but none is needed because the schema carries the full burden.

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 opens with 'Liste des recherches sauvegardees de l'utilisateur', stating a specific action (list), a specific resource (saved searches), and user scope. This clearly differentiates it from siblings like create_saved_search and list_watched_companies.

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 'Utiliser cet outil' section explicitly states when to use it: before create_saved_search to avoid duplicate names, and to answer questions like 'quelles veilles ai-je ?'. It names the sibling alternative and the conditions that select this tool.

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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