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l0g.fr Risk Intelligence

Get Agent Manifest

get_agent_manifest
Read-onlyIdempotent

Renvoie le manifeste Agent Surface de l0g.fr : capacités, endpoints, règles d'usage, politiques de preuve et compteurs. Point d'entrée recommandé pour découvrir les surfaces machine sans scraper.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
errorNo
countsNo
serverNo
versionNo
endpointsNo
descriptionNo
proofPolicyNo
capabilitiesNo

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint=false, idempotentHint, and non-destructive behavior. The description adds useful context about what the manifest contains and positions it as a non-scraping discovery path, but it does not disclose additional behavioral details such as caching, versioning, or stability.

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?

Two concise, front-loaded sentences. The core return value is stated first, followed by content details and the recommended usage context. Every part earns its place with no redundancy.

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 zero-parameter, read-only, idempotent tool with an output schema and annotations covering safety, the description provides enough context to select and invoke the tool correctly. It also adds a clear discovery-oriented framing that helps the agent understand when to call it.

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?

The tool has zero parameters, so the schema already covers everything. The description adds no parameter information because none is needed; the baseline of 4 applies cleanly here.

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 states a specific verb ('Renvoie' / returns) and a specific resource ('le manifeste Agent Surface de l0g.fr'), and enumerates its contents: capabilities, endpoints, usage rules, proof policies, and counters. It clearly indicates what the tool does, though it does not explicitly contrast it with sibling tools by name.

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 recommends this tool as the entry point for discovering machine surfaces and even frames it as an alternative to scraping ('sans scraper'). It gives clear when-to-use context, though it does not mention specific sibling alternatives or exclusions.

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.