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

With no annotations, the description carries the full burden and does disclose useful behavioral traits: date format (YYYY-MM-DD), a sentinel value ('unverified') when the snapshot could not confirm a date, and a disclaimer that output is information rather than advice. It does not address read-only status or data source freshness, but for an informational lookup tool the disclosure is strong.

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 purpose is front-loaded in the first clause, but the first sentence becomes a dense, parenthetical enumeration of returned content that is hard to scan. The subsequent sentences about date format and the disclaimer are useful, but the overall structure is cumbersome.

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?

Because no output schema exists, the description must describe return values, and it does list the date, article, wording, conditions, related dates, and postponement history. It also explains the date format and the 'unverified' marker. The only gap is that it does not clarify whether the tool is read-only, though no annotations exist to contradict.

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 coverage is 100%, so the schema already documents the single operator_type parameter and its accepted values. The description adds only the phrase 'by operator type,' which conveys no syntax or meaning beyond what the schema provides, making the baseline 3 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?

The description names a specific resource—the application dates of Regulation (EU) 2023/1115 by operator type—and enumerates the content returned (article, wording, conditions, related dates, postponement history). It does not differentiate itself from sibling tools such as eudr_scope or country_risk, but its subject matter is unmistakable without opening the schema.

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 or when-not-to-use guidance and no named alternatives. The reader can infer that it is for looking up obligation dates by operator type, but the description never states a task context or prerequisite for selecting this tool over its siblings.

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 disclosure burden and does well: it names the data provenance (a dated CELLAR snapshot), warns that superseded or not-yet-applying entries are included, and adds a scope disclaimer ('Information, not legal advice'). It leaves silent the read-only nature, error behavior for bad commodity/date input, and response shape, so it is strong but not complete.

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 dense sentence, front-loaded with the resource and regulation, with every clause naming a distinct piece of returned content. It is somewhat run-on but has 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 the return payload, and it does so concretely (CN codes, flags, descriptions, exclusions, later/replaced entries, notes) along with source and date semantics. The main gap is date-validation edge cases, which the input schema partially covers.

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 coverage is 50%: the date parameter is well documented in the schema, while commodity has only an enum with no per-value description. The description restates the seven commodity values already present in the enum and adds the 'on a date' framing, so it adds little beyond the structured fields.

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 resource (all Annex I entries of one commodity under Regulation (EU) 2023/1115) and enumerates exactly what is returned: CN codes, 'ex' flags, Annex descriptions and exclusions, later/replaced entries, and table notes. An agent knows precisely what this tool yields without opening the schema.

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 use case (need Annex I CN codes for a given commodity and date) but never states when to prefer this over the sibling eudr_scope or application_dates, nor any when-not condition. Usage is inferable from the content listing rather than stated.

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 data provenance ('dated CELLAR snapshot'), defines edge-case behavior for territories recorded under another country and unmatched inputs (with suggestions), and includes a disclaimer. It does not explicitly state read-only nature or error-handling beyond unknown_country, keeping 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 dense and front-loaded with the core purpose, then unpacks return values and input formats. Every clause adds information, though the single paragraph is long for a one-parameter lookup; structure is acceptable but not maximally crisp.

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 and no annotations, the description fully explains the possible return values and their conditions, the accepted input formats, the data source, and a legal disclaimer. An agent has everything needed to call the tool and interpret its output correctly.

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% and the schema already gives concrete examples ('BR', 'BRA', 'Brazil', 'Viet Nam'). The description adds the formal standard names (ISO 3166-1 alpha-2, alpha-3, English name), which is useful but minimal; baseline 3 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?

The description names the specific resource (Commission-assigned country risk level under Article 29 of EUDR) and enumerates the exact return values (low, high, standard, not_determined, unknown_country). This is unmistakably distinct from the sibling tools, which cover commodity codes, scope, dates, and sources.

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?

Usage is implied by the return-value semantics and input format, but there is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. The agent must infer that this is the lookup tool for country risk classification.

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 largely succeeds: it discloses the data source (dated CELLAR snapshot, consolidated text plus amending acts), what the returned fields are (commodity, Annex entry text, later/removed entries, legal acts, date checked), and the accepted code formats. It stops short of noting any caching, latency, or ambiguity-resolution behavior, but for a read-only information tool this is close to complete.

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?

Front-loaded with the core question, then return values, then accepted formats and the disclaimer. Dense but every clause carries information; the only mild cost is a long run-on enumeration of statuses.

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 must explain return values and it does so thoroughly, enumerating all four status values and the accompanying payload fields. An agent has everything needed to call it and interpret the result.

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 coverage is 100%, so the baseline is 3. The description adds genuine value beyond the schema by specifying accepted digit lengths (2, 4, 6, 8, 10) and the multiple separators it tolerates, which the schema only hints at with one example.

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 question it answers (is a CN code a relevant product under EUDR 2023/1115) with a clear verb+resource, and enumerates the exact statuses it returns. It is unmistakably distinct from siblings like commodity_codes, country_risk, or application_dates.

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?

Usage is implied by the stated question and the explicit boundary 'Does not classify goods', which tells the agent this is a lookup, not a classifier. However, it never names or contrasts an alternative tool, so the agent must infer when eudr_scope is preferred over siblings.

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 must carry the behavioral burden. It helpfully lists the exact provenance fields returned (CELEX numbers, consolidation status, SHA-256 hashes, verification status, licence), but it does not state that the operation is read-only, whether it has side effects, or any authentication requirements.

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 a single, dense sentence that front-loads the core concept ('The legal acts behind every answer') and then lists fields. It is concise with no filler, though the run-on list could be better structured for scanning.

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 zero-parameter, no-output-schema tool, the description does a good job enumerating the returned fields, which is the main thing an agent needs to know. It still lacks explicit invocation context and output format details, but the low complexity keeps the gap modest.

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, so the baseline score is 4. The description appropriately focuses on return content rather than input semantics, though it could clarify the output structure.

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 identifies the resource as 'the legal acts behind every answer' and enumerates the metadata fields returned, so an agent can infer it retrieves provenance data. However, it lacks a clear action verb (e.g., 'Retrieve' or 'List') and does not explicitly differentiate itself from sibling tools like commodity_codes or country_risk.

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 guidance on when to use this tool versus alternatives, no prerequisites, and no conditions for invocation. The phrase 'behind every answer' hints at a citation use case but does not state it explicitly.

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