dd

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

Annotations declare readOnlyHint and openWorldHint. The description adds value by detailing threshold risk categories and the compliance tier requirement, providing behavioral clarity beyond 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 a single compact sentence followed by a clear threshold list. Every sentence earns its place, no fluff, and critical info 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?

For a simple one-parameter tool with no output schema, the description adequately covers input and risk categories. It lacks explicit return format details but is sufficient for an agent to understand and invoke the tool.

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 100% schema coverage, the description adds little to the single 'ico' parameter beyond what the schema already provides. It explains the tool's operation but not parameter specifics. 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 clearly states the tool detects 'shell-firm hotel' patterns by counting shared addresses, with explicit risk thresholds. The title and description make the purpose unmistakable and differentiate it from sibling detection tools.

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 tool implies usage for address-based risk assessment, but fails to explicitly state when to use it over siblings like detect_nominee_director or detect_phoenix. No guidance on exclusions 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?

Annotations include readOnlyHint and openWorldHint. The description adds that it uses ARES data and returns a breakdown with riskScore 0-100, which is valuable beyond annotations. No contradiction. Could mention limitations like no ISIR cross-reference.

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, front-loaded with purpose, then details. No redundant 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?

Explains output (indicator breakdown, riskScore) and indicators. No output schema, but description is sufficient. Could mention error handling for invalid ICO, but minor omission given low complexity.

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 baseline 3. The description does not add additional meaning to the 'ico' parameter beyond what the schema 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 it detects nominee director patterns, lists three specific indicators (age outlier, multi-board membership, recent appointment), and distinguishes from the sibling tool 'detect_nominee_director_rich'.

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 mentions 'Pro Compliance tier or higher' as a prerequisite and directs to the rich variant for deeper analysis, providing clear context and an alternative. It does not explicitly state when not to use, but the alternative serves that purpose.

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 description adds context beyond annotations by specifying data sources (ARES+ISIR), the three surface indicators, and access tier (Pro Compliance), complementing the readOnlyHint and openWorldHint 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 extremely concise (two sentences), front-loaded with the core purpose, and every sentence adds necessary information 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 single parameter, clear output (PhoenixReport with riskScore 0-100), and annotations, the description provides sufficient context for an AI agent to correctly invoke and interpret the tool.

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 'ico' as 'Czech IČO — 7 or 8 digits'. The description adds no further parameter semantics beyond what the schema 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 verb 'Detect' and resource 'phoenix company pattern', lists specific indicators, and distinguishes from a richer alternative (detect_phoenix_rich).

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 mentions when to use (for 3 surface indicators) and directs to detect_phoenix_rich for deeper analysis, providing clear guidance on tool selection.

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?

Annotations provide readOnlyHint and openWorldHint. The description adds behavioral context by detailing what the report includes (risk score, sanctions check) and the depth parameter's impact. No contradictions found.

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, well-structured sentence that covers key aspects. It is concise but might benefit from splitting into bullets for readability. No superfluous content.

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 two well-documented parameters and no output schema required, the description sufficiently explains the tool's capabilities and outputs. It stands on its own among sibling tools without needing additional context.

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 descriptions for both parameters. The description adds nuance by explaining the 'depth' enum values ('basic' vs 'full') in natural language, aiding selection beyond the schema's enum labels.

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 complete due-diligence report for a Czech IČO and enumerates specific outputs (company facts, statutory body sanctions, risk score). This distinguishes it from sibling tools like detect_nominee_director or get_risk_score, which focus on 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 the tool is for overall due diligence, but does not explicitly state when to use it vs. alternatives. Sibling tools are listed but no direct guidance on selection criteria or when to prefer this over more specialized 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?

Annotations declare readOnlyHint: true and openWorldHint: true. The description adds valuable behavioral context: returns GLEIF entity data (status, address, registration number) plus sanctions screening, coverage notes per country, and SME limitations. This transparency goes beyond the 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?

Four sentences, front-loaded with purpose. Each sentence adds value (input format, output summary, coverage notes, tier requirement). Could be slightly more concise, but 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?

No output schema exists, so description must explain return values. It does so by listing GLEIF data fields and sanctions screening. It also mentions coverage notes and SME limitations. For a 2-param tool, this is sufficiently complete 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%, but the description adds meaning: explains identifier accepts 20-char LEI or company name, and country narrows name search. This helps the agent understand the flexible input format beyond the schema's basic 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 generates an EU Due-Diligence report with GLEIF data and sanctions screening. It specifics inputs (LEI code or company name+country) and outputs. This distinguishes it from siblings like get_dd_report by targeting EU and using GLEIF coverage.

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 clear input guidance (LEI code vs. company name, optional country), notes tier requirement (Pro Compliance), and warns about SME coverage. However, it does not explicitly state when to choose this over sibling tools like get_dd_report or get_eu_parent.

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 description discloses the multi-step lookup (ARES then GLEIF), the return of a confidence level, and coverage limitations. Annotations provide readOnlyHint and openWorldHint, and the description adds behavioral context without contradiction.

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 concise and well-structured: it starts with the main purpose, explains the process, then notes limitations and requirements. Every sentence provides 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 single parameter and lack of output schema, the description adequately explains inputs, outputs, and limitations. It also mentions the tier requirement. Minor improvement would be to note if there are any pagination or rate limits, 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?

The schema coverage is 100% and the description of the 'ico' parameter ('Czech IČO — 7 or 8 digits') aligns with the schema. The description adds no additional semantics beyond what the schema provides, so a baseline score of 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 clearly states the tool's purpose: finding the EU/international parent company for a Czech IČO. It specifies the process (ARES then GLEIF) and the outputs (LEI, name, country, confidence). This distinguishes it from sibling tools like detect_phoenix or get_statutory_chain.

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 explains when to use the tool (for finding EU/international parents) and notes limitations (SMEs without LEI won't be found) and a requirement (Pro Compliance tier). While it doesn't explicitly exlude alternatives, the context of sibling tools makes the usage clear.

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?

Annotations already declare readOnlyHint and openWorldHint. Description adds context about the limited return subset (score, level, flags) and speed, which goes beyond 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?

Two sentences, no wasted words, front-loaded with key differentiator and return details.

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 1 param and no output schema, the description sufficiently explains functionality and usage context.

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 description 'Czech IČO — 7 or 8 digits.' The description adds no further meaning; 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?

Clearly states it is a lightweight version of get_dd_report, returns numeric score (0-100), risk level, and top triggered red flags. Distinguishes from sibling tool get_dd_report.

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?

Explicitly says 'Faster when you only need a yes/no/maybe screen', telling when to use this tool vs the heavier get_dd_report. Names the alternative.

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?

Annotations already declare readOnlyHint and openWorldHint; description adds value by listing the types of events included (insolvency, sanctions, VAT flips) and confirms return structure with riskScore, consistent with read-only nature.

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 with no wasted words: first delivers core functionality, second adds usage tier and alternative. Front-loaded with key 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 simple input (1 parameter) and no output schema, the description adequately covers purpose, inputs, constraints, and return shape (events with riskScore). Provides enough context for an agent to select and invoke 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 covers the single parameter (ico) with description about format (7-8 digits). Description does not add extra meaning beyond the schema, so baseline of 3 applies given 100% schema 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?

Clearly states it builds a chronologically sorted lifecycle timeline for Czech companies, listing specific event types (formation, appointments, etc.) and distinguishes itself from the sibling get_risk_timeline_rich.

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?

Specifies required tier (Pro Compliance or higher) and explicitly directs to the enriched alternative for more detailed needs. Does not provide explicit when-not-to-use but gives sufficient context through the alternative.

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 description discloses behavioral traits beyond annotations: it is a heuristic, noisy for common surnames, and auto-skips persons with common surnames with a SURNAME_TOO_COMMON note. Annotations already declare readOnlyHint and openWorldHint, and the description adds context about the tool's limitations and behavior.

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 paragraph that efficiently conveys all key points. It is front-loaded with the core purpose and includes critical usage notes. While not overly long, it could benefit from bullet points for readability, but it is well-structured and 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 the tool's complexity (heuristic walk, 2 params, no output schema), the description provides complete context: purpose, limitations, when to use, when not to use, alternative tools, and expected behavior (auto-skip for common surnames). 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?

Schema description coverage is 100% with both parameters (ico and max_depth) already documented. The description adds context about the heuristic nature and surname rareness, but does not provide additional parameter-specific meaning beyond the schema. 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 clearly states it performs a 'surname-based heuristic walk through statutory bodies of related Czech companies'. It distinguishes from siblings by explicitly stating it is not a true UBO source and referencing the alternative ESM tool.

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 specifies when to use ('best for shell-company unwinding in small s.r.o. with RARE surnames') and when not to use (for actual beneficial ownership, or for common surnames like Novák). It also names the alternative tool (ESM) and explains the auto-skip behavior for common surnames.

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?

Annotations declare readOnlyHint=true, and the description aligns by noting 'Stub only — persists nothing yet.' It adds significant behavioral details: statuses, flags, a human-only onboarding URL, and a caution not to interact with the link. No contradictions.

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-loading the purpose and key behavioral notes. Every sentence adds value, with no redundancy or fluff.

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), the description adequately covers return structure, stub nature, and user actions. Minor omission: no explicit error handling or input validation beyond the schema.

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 'ico' parameter, and the description doesn't add meaning beyond what the schema already provides (7-8 digit IČO). Baseline score of 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 clearly states the tool's purpose: starting onboarding for free monitoring of a Czech company by IČO. It distinguishes itself from sibling tools that focus on detection and reports, making its function unique.

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 context for monitoring but doesn't explicitly state when to use versus alternatives. No direct exclusions or when-not guidance is provided, leaving it somewhat implied.

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