AGORA Omega

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

No annotations are provided, so the description carries the full burden. It does disclose the critical behavioral trait of cost and payment mechanism ($0.02 USDC per call via x402) and hints at the response content, but omits auth requirements, rate limits, or what happens with the supplied text.

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

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

A compact two-clause sentence that front-loads the regulatory purpose before the output scope and pricing. No padding, though the pricing clause is appended without a clear lead-in about sequencing.

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

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

With no annotations, no output schema, and four undocumented parameters, the description should do more. It states what the tool returns at a high level but leaves the meaning of every input unexplained, which is the main gap an agent would hit when actually invoking it.

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

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

All four parameters (texte, langue, contexte, relu_par_humain) have 0% schema description coverage, and the description says nothing about any of them — not even that texte is the input under review or what langue/contexte control. The description does not compensate for the total gap in input documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: an 'EU AI Act art. 50 transparency check' that determines whether AI disclosure is required, whether it is present, and supplies the disclosure text plus machine-readable metadata. The purpose is precise and clearly distinct from catalog/search/audit siblings, though it never names a sibling to contrast with.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the compliance context (EU AI Act art. 50) but gives no explicit when-to-use guidance, no prerequisites, and no alternatives or exclusions. An agent has to infer the triggering situation entirely from the purpose sentence.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

No annotations are provided, so the description carries the burden. It does add real behavioral context beyond the schema: the call is free, and payment for the listed tools is in USDC via x402. It does not state that the operation is read-only/no-side-effect, nor describe the shape or volume of the returned catalog.

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

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

A single tight sentence with the most decision-relevant fact ('Free.') front-loaded. No filler and nothing restated from the name.

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

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

For a no-parameter, no-output-schema catalog tool the description covers what the tool returns and the cost/payment model, which is what an agent needs to select it. Minor gaps remain: no mention of networks covered or the response format.

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

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

The tool takes zero parameters and schema coverage is 100%, so there is nothing for the description to disambiguate. Baseline 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Lists') and resource ('AGORA Omega paid tools, prices and networks'), which is clearly distinct from the check/audit/verify siblings. It does not explicitly name a sibling to contrast with, but the catalog role is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage: call this to discover what paid tools and networks exist and what they cost. There is no explicit when-to-use vs alternatives guidance, and no statement of prerequisites, though for a zero-argument discovery tool this is largely self-evident.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full behavioral burden, and it does disclose a genuinely useful trait: the per-call cost ($0.01 USDC via x402), which is payment/auth context not present in the schema. It remains silent on rate limits, matching behavior, and error handling, so coverage is partial.

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

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

Two compact sentences: the first front-loads what data is returned, the second front-loads the cost. Nothing is wasted and the most decision-relevant facts lead.

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

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

With no output schema, the description helpfully enumerates the returned fields, which covers part of the output burden. But with no annotations and no usage guidance, an agent still lacks information on when this beats sibling tools and how results are shaped (ordering, pagination).

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

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

Schema description coverage is 100%, so every parameter (q, naf, limite, departement) is already documented in the schema. The description adds no syntax, matching, or formatting detail beyond it, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a concrete resource — official French company data from SIRENE/RNE — and enumerates the fields returned (identity, geolocated HQ, NACE, headcount, revenue, net income), so an agent knows exactly what this yields. However the action verb is only implied by the tool name 'search', and it does not distinguish itself from siblings like agora_counterparty_check or agora_supplier_audit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use guidance and no mention of alternatives. Given related siblings such as agora_counterparty_check and agora_supplier_audit, the absence of routing guidance leaves the agent to guess which company-data tool to select.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the burden and does disclose material operational traits: data provenance (official public data), freshness (refreshed daily), and commercial cost ($0.08 USDC per call paid with x402) — the cost/payment detail is genuinely useful for agent invocation. It omits any statement of what a result looks like (hit vs. clear) or latency, which keeps it from a 5.

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

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

Three tight sentences: purpose and trigger first, then the data sources, then cost/freshness. The trigger and scope are front-loaded and no sentence is filler.

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

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

For a read-only lookup with no output schema and no annotations, the description supplies scope, sources, freshness, and price — enough to invoke it confidently. It leaves the response shape (matching fields, risk verdict) unspecified, which is a minor gap given no output schema exists to cover it.

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

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

Schema description coverage is 100%, with both 'nom' (legal or brand name) and 'site' (website or domain) documented in the schema itself. The description adds no syntax, format, or matching-behavior detail for these inputs, so the baseline 3 for schema-covered parameters is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Counterparty check before paying a platform or crypto provider') and enumerates exactly which datasets are consulted (AMF blacklists, ESMA MiCA register, EU/UN/OFAC sanctions). This differentiates it from siblings like agora_company_search (general lookup) and agora_supplier_audit (broader audit).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear trigger context: run it before paying a platform or crypto provider. That is a concrete when-to-use. It does not, however, name an alternative tool or state exclusions (e.g., what to use instead for non-payment due diligence), so it stops short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full behavioral burden and does well: it names the aggregated data sources, the merged decision output, the confidence score, the exact price, and the x402 payment mechanism. It does not disclose read-only status, freshness or latency characteristics, or error behavior, which keeps it from a 5.

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

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

The description is two sentences and front-loads the core purpose before listing sources and the price. The first sentence is dense but every clause contributes relevant information, and there is no filler.

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

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

There is no output schema, so the description must describe return values, and it does: a merged pay/verify/do-not-pay decision with confidence score. Combined with the price and payment protocol, this is enough for an agent to decide to invoke it, though wallet setup and failure modes remain unspecified.

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

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 all four parameters clearly. The description adds no parameter-level semantics such as format expectations for 'siren' or 'site', which is acceptable but unremarkable; baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: an orchestrated supplier due-diligence mission that merges French registry, AMF, ESMA MiCA, and sanctions data into a pay/verify/do-not-pay decision with a confidence score. It does not explicitly name or contrast itself with the closest sibling, agora_counterparty_check, so it falls just short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context: 'Run it before paying a supplier or platform.' That is a direct when-to-use trigger and goes beyond mere implication. However, it provides no when-not-to-use guidance or explicit alternatives among the sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

With no annotations, the description carries the full burden and does well: it discloses the cost model ($0.05 USDC per call via x402), the independence of the verifier, and the shape of the result including the three verdict labels. It omits latency/rate limits and error behavior, which keeps it short of a 5.

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

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

Four compact sentences, front-loaded with what it is and what you get, followed by when to use it and the price. No filler, though the verdict glossary and pricing could be tightened.

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

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

No output schema or annotations exist, so the description rightly supplies the return semantics (score range, doubtful claims, verdict vocabulary) and the payment model. Input constraints live in the schema, so nothing critical is missing for correct invocation.

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

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

Schema description coverage is 100%, so texte, langue and consigne are already fully documented, including the 12,000-char limit and fr/en choice. The description adds no parameter-level detail beyond that, which meets the baseline for a fully-covered schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('independent verifier agent' that checks a deliverable) and enumerates the outputs (0-100 score, doubtful claims, verdict mapped to valider/corriger/rejeter). It is clearly distinguishable from the sibling audit/check tools, though it never names or contrasts them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Check another agent's work before paying for it' gives a concrete triggering condition for use. There is no explicit when-not guidance or named alternative among the siblings, but the context is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.