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l0g.fr Risk Intelligence

Get Claims

get_claims
Read-onlyIdempotent

Interroge les trois relations affirmation-source structurantes au maximum par article l0g. Filtrage par article, type de claim (fait, estimation, inférence ou scénario) et texte. Renvoie les références cliquables, datées quand détectable.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNoType de claim optionnel.
limitNoNombre maximum de claims.
queryNoFiltre texte optionnel dans la claim ou le titre article.
claimIdNoIdentifiant exact pour obtenir une claim unique.
languageNoLangue du slug fourni. Une claim reste canonique en français.
sourceIdNoSlug de source, nom ou hôte cité.
articleSlugNoSlug d'article optionnel.
includeEvidenceNoInclut le voisinage de preuve quand une seule claim est renvoyée.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
errorNo
claimsNo
policyNo
sourceNo
claimIdNo
filtersNo
versionNo
evidenceNo
sourceIdNo
claimKindsNo
directEvidenceNo
relatedContentNo

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds useful behavioral context by stating that references are clickable and dated when detectable, which goes beyond the annotations without contradicting them.

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 concise, with two sentences and the main action front-loaded. It earns a 4 rather than 5 because of the cryptic 'trois relations affirmation-source structurantes' wording and the 'l0g' typo, which force extra parsing effort.

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

Completeness4/5

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

With a complete input schema, output schema, and annotations, the description does not need to re-explain parameters or return structure. It provides enough orientation for an agent to understand the tool's purpose and main filters, though the ambiguous relationship phrase and typo leave some room for improvement.

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 all 8 parameters already have descriptions in the schema. The tool description only names three filter dimensions and adds no extra constraints, defaults, or interplay between parameters, so the baseline 3 is appropriate.

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 uses a specific verb ('Interroge') and identifies the resource (claim-source relations) plus the main filter dimensions (article, claim type, text) and output (clickable references). It is mostly clear, but the phrase 'trois relations affirmation-source structurantes' and the apparent typo 'l0g' keep it from being fully unambiguous.

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 explicitly names the key filtering contexts: article, claim type, and text, which gives an agent a clear sense of when to call this tool. It does not mention when not to use it or point to sibling alternatives, so it falls short of a 5.

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

A3.9/5.0
Disambiguation4/5

Most tools target clearly distinct resources (articles, claims, sources, indices, signal history, integrity), and the descriptions are detailed. The two real ambiguities are get_changefeed vs get_changes, which are near-identical except for filtering, and the Agent Surface metadata cluster (manifest, openapi, integrity, verify, ndjson feed) where an agent could misselect. These are minor enough not to undermine the set.

Naming Consistency5/5

All 21 tools follow a consistent verb-first snake_case pattern with clear semantic verbs: get_ for retrieval, list_ for enumeration, search_ for querying, plus build_research_pack and verify_artifact as lone but clearly communicative composites. There is no mixing of conventions or vague verbs like process or run, making tool selection predictable.

Tool Count4/5

21 tools is above the ideal 3-15 range, but the server covers a broad domain: content retrieval, claims and evidence graphs, risk signals, change monitoring, and integrity verification. A few tools could be consolidated (the changefeed pair and the metadata cluster), but none is pure filler, so the count feels justified though slightly heavy.

Completeness4/5

For a read-only intelligence platform, the coverage is comprehensive: content listing and full-text retrieval, claims and evidence graphs, source auditing, risk indices with history, freshness and risk-diff monitoring, and artifact verification. Minor gaps include no per-source detail endpoint and no push or subscription mechanism, but agents can work around these using list_sources and the changefeed.