healthguard

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

With no annotations provided, the description must convey behavioral traits. It indicates the tool generates a template (non-destructive), but does not disclose whether it accesses or modifies any data, requires authentication, or produces any side effects. The description is adequate for a generation tool but leaves gaps about system interactions.

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 consists of two concise sentences: the first delivers the core purpose, the second adds essential context (regional obligations). No redundant information is present, and the critical detail is front-loaded.

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?

Given the lack of output schema and annotations, the description is moderately complete. It specifies the tool’s function and relevant regulatory standards, but does not describe the output format, return type, or how the generated template should be used. For an agent, this is sufficient to select the tool but not to execute it without inference.

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% (severity and reporter_type have descriptions; drug_name and event_description do not). The tool description does not add any parameter-specific meaning beyond the schema, nor does it compensate for the undocumented parameters. This leaves ambiguity for the two unnamed parameters.

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 clearly states the verb 'generate' and the resource 'adverse event report template', and specifies the standard (MedDRA) and regulatory contexts (EU/DE/US). It effectively distinguishes this tool from its siblings, which cover unrelated domains like device classification or drug interaction.

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 use for pharmacovigilance reporting with specific regional obligations, but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites. The siblings are sufficiently different that misuse is unlikely, but explicit guidance could improve clarity.

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 full burden. It discloses the scope (Phase I-IV, CTIS, German specifics) but does not explain the behavior (e.g., returns structured text or a list). No contradictions with annotations.

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, concise and front-loaded with the key information. It could be slightly more specific by adding a verb, but overall it is efficient.

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?

Given the lack of output schema and annotations, the description conveys the tool's purpose but lacks details on return format or example outputs. For a simple lookup tool with one parameter, it is minimally complete but could be improved.

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 base is 3. The description does not add meaning beyond the schema's parameter description; it only repeats the phase names. For a single-parameter tool, this is adequate.

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 clearly states the tool provides clinical trial phase requirements under EU CTR 536/2014, covering Phase I-IV and German specifics. It is specific about the resource (clinical trial phases) and regulation, and distinguishes itself from sibling tools like adverse_event_report or mdr_compliance_check.

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 tool is to be used when looking up clinical trial phase requirements under EU CTR, but does not explicitly state when to use it or when not to use it. No alternative tools or exclusions are mentioned.

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. It correctly describes the tool's purpose but does not disclose behavioral traits such as determinism, handling of missing inputs, or side effects. It is adequate but lacks depth.

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 concise sentences deliver the essential purpose without extraneous information. Every sentence adds value.

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 classification tool with 9 optional boolean inputs, the description is complete in stating the output classes but lacks details on required parameters, default behavior, or interpretation of partial input. No output schema exists, so more context would be beneficial.

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 only 11%, and the description does not elaborate on the meaning or combinations of the 9 input parameters beyond the schema. It fails to compensate for the low coverage.

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 clearly states it performs MDR Annex VIII medical device risk classification, explicitly listing the output classes I/IIa/IIb/III. The verb 'determines' and resource are specific, and it is distinguishable from siblings which cover different regulatory topics.

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?

No guidance is provided on when to use this tool vs alternatives or when not to use it. Sibling tools exist but the description does not reference them or offer contextual usage advice.

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?

Discloses that it only checks known high-risk combinations and is not clinical. No annotations to contradict, so description carries full burden and does it adequately.

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 sentences, each essential and front-loaded. No wasted words.

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 simple tool with one parameter and no output schema, the description covers purpose, limitations, and scope completely.

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% with a clear description of the 'drugs' parameter. The tool description adds no additional parameter details beyond the 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?

Clearly states the tool checks basic drug-drug interaction risks, is educational, and not clinical. Distinguishes from siblings like adverse_event_report or clinical_trial_phases.

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?

Provides a strong caveat that it is educational and not a clinical decision system, but does not explicitly compare to other tools or advise when exactly to use it.

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 must bear the burden. It states the tool 'Returns required legal basis, DPIA requirements, retention periods,' implying a read-only operation. However, it does not disclose potential behaviors like required permissions, rate limits, or whether it modifies data. The description provides basic behavioral context but lacks completeness.

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, concise sentence that immediately conveys the tool's purpose and expected outputs. No unnecessary words or repetition.

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?

The description covers the tool's purpose and key outputs (legal basis, DPIA, retention periods) but lacks details on output format, interpretation, or any prerequisites. Given no output schema, more detail on the results would improve completeness. It is adequate for a straightforward assessment tool but leaves gaps.

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 67% (two of three parameters have descriptions in the schema). The tool description does not elaborate on parameter usage beyond the schema. It adds context about the output but not about inputs, so it neither compensates for the undocumented parameter nor adds significant value over the 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?

The description clearly states it is for GDPR Art.9 health data processing compliance assessment, specifying the regulation (Art.9) and data type (health data). It distinguishes itself from sibling tools like hipaa_vs_gdpr or mdr_compliance_check by targeting a specific GDPR article and health data.

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 use for health data processing compliance under GDPR Art.9, but does not provide explicit guidance on when to use this tool versus alternatives (e.g., hipaa_vs_gdpr for comparison, mdr_compliance_check for medical devices). No exclusions or prerequisites are mentioned.

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 provided, and the description does not disclose behavioral traits beyond the tool's content. It does not mention side effects, authentication needs, or what the output looks like.

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?

Single sentence that is concise and front-loaded with the core purpose. No wasted words; every word earns its place.

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 should explain what the tool returns, but only says 'audit checklist' without format or detail. Given the single parameter and clear subject, it is minimally adequate but leaves gaps for an agent.

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% since the parameter has a description in the schema. The overall description adds no additional meaning to the parameter beyond what the schema already provides.

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 clearly states the tool provides a GMP audit checklist per EU EudraLex Vol.4, covering specific areas (QMS, personnel, etc.), which distinguishes it from sibling tools like clinical_trial_phases or drug_interaction.

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?

No guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description does not help an agent decide between gmp_checklist and similar regulatory 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?

No annotations are provided, so the description carries full burden. It states it provides analysis and tips, but does not disclose output format, whether it is static or dynamic, or any behavioral traits. Minimal behavioral context.

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 sentence, 12 words, front-loaded with the core topic. Every word adds value; no redundancy.

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?

Given no parameters, output schema, or annotations, the description adequately communicates the tool's purpose but lacks details on how the comparison is presented (format, interactivity) or how current it is. Adequate but not thorough.

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 has no parameters, so the description does not need to add parameter meaning. A baseline score of 4 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 clearly states the tool provides a comparison between HIPAA and GDPR for healthcare organizations with side-by-side analysis and dual-compliance tips. It distinguishes itself from sibling tools like gdpr_health_check. Specific verb 'comparison' and resource 'HIPAA vs GDPR' are clearly identified.

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 usage for comparing two regulations but does not explicitly state when to use it versus alternatives like gdpr_health_check or mdr_compliance_check. No guidance on prerequisites or when not to use.

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 disclose behavioral traits. It notes 'covers common codes' (implying incompleteness) and 'uses ICD-10-GM' (a specific dialect), which adds context. However, it does not state that it is read-only, idempotent, or any other behavioral traits. For a lookup tool, the non-destructive nature is implied but not explicitly stated.

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, front-loaded with the primary purpose, and every sentence adds value. No extraneous information. Highly concise and structured.

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?

The description is adequate for a simple look-up tool, but lacks information about return format, behavior when no parameters are provided (e.g., returns chapter overview as hinted), and does not specify whether both parameters can be used together or exclusivity. Given the lack of output schema, some additional guidance on response structure would improve completeness.

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% with both parameters described. The description adds value beyond schema by noting the scope ('common codes', 'chapter overview') and language variant (German Modification), which clarifies the database's limitations and dialect beyond the parameter definitions.

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 clearly states it is for ICD-10 code lookup and search, and specifies it covers common codes and chapter overview using the German Modification. This distinguishes it from sibling tools which are about regulatory compliance and clinical trials, not ICD codes.

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 usage for looking up or searching ICD-10 codes, but provides no explicit guidance on when to use this tool versus alternatives, nor any conditions or exclusions. Since no sibling tool performs ICD lookup, the need for guidelines is lower but still absent.

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, and the description does not disclose behavioral traits like whether the tool performs validation, retrieves information, or modifies data. The term 'compliance' is vague, and no side effects or required permissions are mentioned.

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, concise sentence covering key aspects. It is front-loaded with the regulation identifier, avoids redundancy, and packs useful information efficiently.

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?

Given the absence of an output schema and annotations, the description fails to explain what the tool returns (e.g., a pass/fail status, detailed list of requirements). It also does not clarify whether parameters are required or how they are used together.

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?

Only one of two parameters (risk_class) has a schema description, which the tool description echoes but does not enrich. The device_name parameter has no description in schema or tool description, leaving ambiguity about its purpose.

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 clearly identifies the tool's domain: EU IVDR 2017/746 compliance for in-vitro diagnostic devices. It specifies risk classes A-D, Notified Body requirements, and transition deadlines, distinguishing it from sibling tools like mdr_compliance_check.

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?

No explicit guidance on when to use this tool versus alternatives such as device_classification or mdr_compliance_check. The description does not mention prerequisites, limitations, or typical use cases.

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 full burden. It states the tool 'checks' and 'returns compliance score', implying a read-only, non-destructive operation, but does not explicitly confirm this or disclose any behavioral traits like authentication needs, rate limits, or side effects.

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 concise sentences front-load the regulatory context (EU MDR 2017/745) and immediately list the core components checked. Every word adds value; 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?

Lacking an output schema and annotations, the description omits critical details: the format or scale of the compliance score, whether any parameters are required, how edges like missing data are handled, and what happens if inputs conflict. While it covers what the tool does, it fails to provide sufficient context for an agent to reliably invoke 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?

With only 22% schema description coverage (2 of 9 parameters documented), the description must compensate but only lists the checked areas without linking them to individual parameters. For example, 'has_ce_mark' is not explained despite being a key input.

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 clearly states it assesses EU MDR 2017/745 compliance for medical devices, enumerating specific checks (CE marking, Notified Body, etc.) and confirms it returns a compliance score. It is distinct from sibling tools like device_classification or udi_validate, which cover narrower aspects.

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 use for MDR compliance assessment but provides no explicit guidance on when to use this tool over alternatives (e.g., ivdr_check, device_classification). No when-not-to-use or prerequisite instructions are given.

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 should disclose behavioral traits such as whether the tool is read-only or requires authentication. It only lists deadline categories but does not explain what the tool does (e.g., returns a list) or its side effects.

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 extremely concise at two sentences, immediately stating the tool's domain. No redundant information; every word adds value.

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?

Given low complexity (one optional parameter, no output schema), the description is adequate but could be improved by specifying the output's nature (e.g., list of dates, deadlines) or behavior (e.g., defaults to current year).

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% for the single parameter 'year', and the description adds context by naming specific regulations. However, it does not elaborate on the year parameter's role or format beyond the schema's description.

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 specifies 'EU healthcare regulatory deadlines' and lists relevant regulations (MDR, IVDR, AI Act), making the domain clear. However, it does not explicitly state the action (e.g., 'list', 'display') that the tool performs, which slightly reduces clarity.

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?

No guidance is provided on when to use this tool versus sibling tools like mdr_compliance_check or gdpr_health_check. The description lacks context for choosing among alternatives.

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 provided, so the description must fully disclose behavior. It states validation and agency identification but does not specify what indicates success/failure, whether it returns a boolean or detailed report, or any error handling details.

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, no extraneous words, and front-loads the core action. Every word earns its place.

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?

Given the simplicity of the tool (one parameter, no output schema, no annotations), the description covers the essential purpose and output. However, it could be more complete by hinting at the return format or behavior on invalid input.

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% for the single parameter, and the description adds value by specifying the regulatory standard (MDR Art. 27) and the issuing agencies identified, which goes beyond the simple schema description.

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 clearly states the tool validates UDI format per MDR Art. 27 and identifies the issuing agency. The verb 'Validate' and resource 'UDI format' are specific, and it distinguishes from sibling tools that cover different regulatory areas.

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?

No explicit guidance on when to use this tool versus other tools. While the name and description imply it's for UDI validation, there is no mention of alternatives or conditions for use.

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