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

No annotations are provided, so the description carries full burden. It includes a comprehensive 'Behavioral Transparency' section covering side effects, authentication, rate limits, error handling, idempotency, and data privacy. All relevant behavioral traits are disclosed.

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 overly verbose with redundant sections (e.g., 'Behavior' repeats content from 'Behavioral Transparency'). While front-loaded with purpose, the structure could be tighter. Several sentences could be consolidated without loss of clarity.

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 that an output schema exists (per context signals), the description does not need to detail return values. It mentions 'executive summary' and explains processing behavior. However, it lacks specifics about the output format, but this is acceptable since the output schema is presumably defined separately.

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 0%, and the description's 'Args' section merely repeats parameter names with generic phrases like 'The entity description to analyze or process.' This adds no meaningful context beyond the schema, failing to compensate for the lack of schema descriptions.

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's purpose: 'Run audits across all 5 DORA pillars and return an executive summary.' It uses a specific verb and resource, and distinguishes from siblings like audit_pillar (likely single pillar).

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 includes dedicated 'When to use' and 'When NOT to use' sections, providing explicit context for usage and alternatives (e.g., not a substitute for legal counsel). This clearly guides the agent on appropriate invocation.

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, but description fully covers: read-only, stateless, idempotent, no side effects, no auth required for basic tier, rate limits (10/day free, unlimited pro), structured error handling, data privacy no storage. Exceeds need for a mutation tool.

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?

Well-structured with clear sections (main, behavior, when to use, args, behavioral transparency). Front-loaded key purpose. Slightly verbose but each section adds value. Could be trimmed slightly but overall efficient for complexity.

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 output schema exists (context signals), the description covers behavior, usage, parameters, rate limits, error handling, idempotency, data privacy, and authentication. Minor ambiguity with api_key parameter vs environment variable. No example output needed due to output schema. Adequate for agent decision-making.

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 0%, but description's 'Args' section merely restates names and types from schema (e.g., 'pillar_number (int): The pillar number to analyze or process'). No added constraints, formats, or examples. 'api_key' description contradicts behavioral transparency which says passed via environment variable. Main text provides some context but parameter descriptions are tautological.

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 'Audit a specific DORA pillar (1-5) against your entity's current controls' with specific verb, resource, and scope. It distinguishes from siblings like audit_all_pillars (all pillars) and list_pillars (just listing). Output includes pass/fail, gap list, and remediation priority.

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?

Explicit 'When to use' and 'When NOT to use' sections. States use for auditing, gap analysis, readiness checks; warns not a substitute for legal counsel. Implicitly differentiates from siblings like audit_all_pillars (full audit) and list_pillars (just listing).

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 provided, the description fully covers behavioral traits: read-only and stateless (no side effects), authentication (none for basic, API key for pro), rate limits (free 10/day, pro unlimited), error handling (structured errors), idempotency, and data privacy. This is comprehensive and exceeds expectations.

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 well-structured with clear sections and front-loaded with key information. However, it contains redundancy: the 'Behavior' paragraph and the 'Behavioral Transparency' section both mention read-only, stateless, rate limits, etc. This duplication adds unnecessary length. More concise organization would improve clarity.

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 purpose, usage, and behavioral details thoroughly. It mentions return values (in-scope status, entity type, etc.), and since an output schema exists, that is sufficient. However, the parameter documentation is severely lacking, leaving a gap in understanding how to provide input. The description does not explain what 'description' means or provide examples, which is a notable omission.

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 input schema has two parameters with 0% coverage, so the description must compensate. However, the description merely repeats parameter names: 'description (str): The description to analyze or process.' This adds no semantic value and does not explain what kind of description is expected or how to format it, making it unhelpful for an agent.

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's purpose: 'Classify a financial entity's DORA applicability + which entity type it is.' It lists specific outputs (in-scope status, entity type, proportionality tier, starting pillars), making the scope well-defined. However, it does not explicitly differentiate from sibling tools like classify_incident; the distinction is only implied by the tool name and context.

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 provides 'When to use' and 'When NOT to use' sections, offering some guidance (e.g., for gap analysis, not legal advice). It does not, however, compare this tool to siblings or specify when to prefer classify_entity over classify_incident or audit_pillar, leaving the agent to infer usage boundaries.

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 provided, the description fully covers behavioral traits: read-only, stateless, idempotent, rate limits (10/day free), no authentication for basic use, error handling, and data privacy. This is comprehensive and beyond what structured fields would convey.

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 well-organized with clear sections, but contains redundancy: the 'Behavior' and 'Behavioral Transparency' sections overlap significantly. The 'Args' list is verbose with repetitive phrasing. Shortening would improve conciseness without losing information.

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 tool's complexity (6 parameters, 1 required), the description covers all necessary aspects: regulatory context, behavior, auth, rate limits, error handling, and output. The presence of an output schema reduces the need to describe return values, but the description still explains the key output (major incident qualification).

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 'Args' section repeats parameter names and adds generic phrases ('to analyze or process') that add no meaningful context beyond the schema titles. With 0% schema description coverage, the description fails to compensate by explaining valid values or DORA-specific meaning, e.g., what constitutes sufficient economic_impact_eur.

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 purpose: classifying an ICT incident against DORA major-incident thresholds per EU regulation, and distinguishes it from sibling tools like classify_entity by focusing on incidents.

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?

Explicit 'When to use' and 'When NOT to use' sections provide clear guidance: use for compliance assessment, not as legal advice. This effectively helps the agent decide when to invoke the tool.

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?

The 'Behavioral Transparency' section comprehensively covers side effects (read-only, stateless, idempotent), authentication (no auth for basic, Pro/Enterprise require MEOK API key), rate limits (10/day free, unlimited Pro), error handling (structured errors), and data privacy (no storage). Since no annotations were provided, the description correctly carries the full burden of disclosure.

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 well-structured with clear sections (Behavior, When to use, Args, Behavioral Transparency) and front-loads the purpose. While it is lengthy, every sentence provides value. Minor redundancy exists (e.g., 'read-only' repeated), but overall it is appropriately sized for the detail needed.

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 tool's purpose (enforcement status and deadlines) and the presence of an output schema, the description covers all necessary context: behavior, usage guidelines, parameters, and transparency. It does not need to explain return values as the output schema handles that. The description is complete for an agent to use the tool 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?

The input schema has one parameter (api_key) with no description, and schema coverage is 0%. The description's Args section adds 'The api key to analyze or process', which provides some meaning, but it is vague about the key's purpose and when it's required (basic usage doesn't need it). This is adequate but not fully informative; it could clarify that the key is optional for basic usage.

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 'current DORA enforcement status + key upcoming deadlines for financial entities', which is a specific verb-resource combination. It distinguishes itself from sibling tools like audit_all_pillars and classify_entity by focusing on enforcement status rather than auditing or classification.

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 explicitly includes 'When to use' (assess, audit, verify compliance) and 'When NOT to use' (not a substitute for legal counsel) sections, providing clear guidance on appropriate usage. This directly helps the agent decide when to invoke this tool versus alternatives, even without naming 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 covers important traits: cryptographic signing (HMAC-SHA256), output includes verify_url and optional PDF, signature is binding, certificate expires in 365 days. It doesn't mention side effects like storage or rate limits, but the core behavior is well disclosed.

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 well-structured with a clear opening sentence, technical details, and an enumerated parameter list. It is informative without being excessively verbose, though the parameter descriptions could be slightly more concise.

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 output format, expiration, and cryptographic binding. It mentions an output schema exists (though not shown), so return values are presumably documented. It lacks explicit prerequisites like needing prior audit data, but the tool's purpose is clear.

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 schema has 0% description coverage, but the description fully explains each of the 6 parameters, including their purpose and format (e.g., findings_csv as comma-separated list, include_pdf_base64 for PDF). This adds critical meaning beyond the schema's bare names and types.

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 generates a cryptographically signed DORA compliance attestation. It specifies the target audience (Pro/Enterprise) and distinguishes from sibling tools like audit or classify, which are clearly different functions.

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 explains the output should be shared with auditors/board/procurement team, implying the tool is used after compliance checks. However, it doesn't explicitly state when to use or exclude alternatives, leaving room for ambiguity.

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?

A dedicated 'Behavioral Transparency' section covers side effects (read-only), authentication (none for basic), rate limits (10/day free, unlimited pro), error handling, idempotency, and data privacy. With no annotations, the description fully bears the burden and does so excellently.

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 well-structured with clear sections, front-loading the purpose and behavior. Every sentence adds value without 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 the tool's simplicity (list pillars) and the existence of an output schema, the description fully explains what the tool does, its behavioral characteristics, and usage context. No gaps remain.

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 only parameter 'api_key' has schema coverage 0%, and the description merely restates it: 'The api key to analyze or process.' It does not explain when to provide it or its effect, failing to compensate for the schema's lack of 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 states: 'List all 5 DORA pillars with article ranges and key obligations.' This is a specific verb (list) and resource (DORA pillars), clearly distinguishing it from sibling tools like audit_all_pillars or classify_entity.

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?

Explicit 'When to use' and 'When NOT to use' sections provide clear context: assessing, auditing, verifying compliance, gap analysis, and not for legal advice. No direct alternative mention, but siblings differentiate.

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 provided, the detailed 'Behavioral Transparency' section covers side effects (read-only, no modifications), authentication, rate limits, error handling, idempotency, and data privacy extensively, fully compensating for the missing 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 well-structured with clear sections (Behavior, When to use, Behavioral Transparency). While lengthy, each part adds value. A minor reduction in redundant phrasing could improve conciseness.

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 presence of an output schema, the description focuses appropriately on usage and behavior. It covers all necessary aspects for a simple template-retrieval tool, though the parameter explanation could be more precise.

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 single parameter `api_key` has no schema description (0% coverage). The description adds that basic usage requires no authentication and pro/enterprise tiers need a MEOK API key via environment variable, but it ambiguously states the parameter is used to 'analyze or process'. More clarity on when the parameter is needed and its exact role would improve this.

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 returns 'the Article 28.3 Register of Information template structure', specifying the exact regulation (Article 28.3) and purpose (compliance template). This distinguishes it from sibling tools focused on auditing, classification, or certificate retrieval.

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 includes explicit 'When to use' (assess, audit, verify compliance, gap analysis) and 'When NOT to use' (not a substitute for legal counsel) sections, providing clear context and exclusions.

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 description fully covers behavioral traits: read-only, stateless, idempotent, rate limits, authentication needs, error handling, and data privacy in dedicated 'Behavioral Transparency' section.

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?

Description is lengthy with redundant sections ('Behavior' and 'Behavioral Transparency' overlap). Well-structured with headings but could be more concise.

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 that an output schema exists (not needing return explanation) and two parameters, the description covers purpose, usage, and behavioral aspects well. Only parameter semantics are lacking, but overall complete.

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 0%, requiring description to compensate. The 'Args' section provides only generic descriptions ('The entity description to analyze') adding little meaning beyond parameter names. No constraints, examples, or formatting details.

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 assesses TLPT readiness and returns scope and requirements, distinguishing it from siblings like audit_all_pillars or classify_entity.

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 explicit when-to-use scenarios (gap analysis, readiness checks) and a clear when-not-to-use (not legal advice). Lacks explicit comparison to sibling tools but context is clear.

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