JobDoneBot

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

Discloses 'Browser-based tool' which hints at execution environment, and specifies output quantity (10 patterns). However, with no annotations provided, the description fails to address data privacy (are titles sent to external APIs?), rate limits, or error behaviors, leaving significant behavioral gaps.

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?

Perfectly compact: one front-loaded sentence covering input, output count, and special feature (CTR). Parenthetical '(Browser-based tool)' adds necessary context without verbosity. 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?

Given zero parameters and no output schema, the description adequately covers the essentials: what goes in (article titles), what comes out (10 variants with scores), and execution context. Missing only output format details (array vs object), but appropriately complete for a simple utility 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?

Description implies the input is '記事タイトル' (article title), adding crucial semantic information to an otherwise empty input schema. Baseline 4 appropriate for 0-parameter tools, with credit for specifying the expected input resource that the schema omits.

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?

Excellent specificity: states the resource (article titles), action (generates 10 patterns), and distinguishing feature (CTR scores). The 'ABテスト' context in the name combined with these details clearly differentiates it from siblings like article-outline-generator or meta-description-generator.

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 clear context through specific capabilities (10 variants, CTR scoring) that implicitly signal when to use it (A/B testing headlines for CTR optimization). Lacks explicit 'when not to use' or named alternatives, but the scope is sufficiently specialized to guide 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?

With no annotations provided, the description carries the full disclosure burden. It adds crucial behavioral context by noting this is a 'Browser-based tool' (indicating it likely opens a UI rather than returning JSON directly) and mentions the reverse calculation capability. However, it lacks details on persistence, authentication requirements, or whether results can be saved/exported.

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 efficiently front-loaded with no waste: one sentence explains the calculation method and formula, a brief clause adds the reverse-calculation feature, and the parenthetical clarifies the delivery mechanism. Every element 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 tool's low complexity (0 parameters, simple calculator function) and lack of output schema, the description provides sufficient context. It explains what is calculated, how it's calculated, and the browser-based delivery method. A mention of output format (HTML/UI vs JSON) would improve it, but it is adequate for the tool's simplicity.

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 zero parameters (empty object), which per guidelines warrants a baseline score of 4. The description adds value by clarifying that PV, CTR, CVR, and 単価 are the conceptual inputs users will provide in the browser interface, compensating for the empty API schema by explaining what data the tool manipulates.

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 calculates monthly income (月収) using the specific affiliate marketing formula PV×CTR×CVR×単価 (Page Views × Click-Through Rate × Conversion Rate × Unit Price). It effectively distinguishes this from sibling financial calculators like bond-yield-calc or investment-simulator by specifying the exact e-commerce metrics used.

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 through the formula (use when calculating affiliate revenue from traffic metrics) and mentions the reverse calculation feature (逆算機能付き) for working backwards from revenue targets. While it lacks explicit 'use X instead for Y' comparisons, the specific formula makes the appropriate use case clear relative to other calculators.

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 carries full burden. The '(Browser-based tool)' disclosure is essential behavioral information indicating an external UI is opened. However, it omits details on data persistence, authentication requirements, or return format.

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?

Concise Japanese description efficiently structured with core function first, use case second, and implementation detail parenthetically. No wasted words, though slightly more detail on the output behavior would strengthen it.

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 zero parameters and no output schema, the description adequately covers the browser-based invocation method but could clarify what data is returned or displayed (e.g., interactive charts vs static data). Sufficient but minimal for a dashboard 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?

Input schema contains zero parameters. Per evaluation guidelines, 0 params = baseline 4. No parameters require semantic documentation.

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

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

Clearly states it manages graphs (グラフ管理) of affiliate rewards, PV, and CVR broken down by project/campaign and month. The 'browser-based' parenthetical and dashboard nature implicitly distinguish it from the sibling calculator tool (affiliate-revenue-calc).

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?

Mentions tax filing (確定申告) as a specific use case, providing contextual guidance. However, it lacks explicit when-to-use/when-not-to-use rules or references to alternatives like affiliate-revenue-calc for calculation-only needs.

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 carries the full disclosure burden. It adds the crucial behavioral context that this is a 'Browser-based tool', indicating it likely opens a web interface for input rather than accepting function parameters. However, it lacks details on return format, whether results are persisted, or error handling 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?

Extremely concise single Japanese sentence efficiently conveys input source, all five output types, and interaction model. Every element earns its place with no redundant phrasing or tautology.

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 zero-parameter simplicity and lack of output schema, the description provides sufficient context for invocation. It adequately explains what the tool produces and how it accepts input (browser-based). A perfect score would require explicit confirmation of what the tool returns (e.g., whether it returns the calculated data to the agent or merely opens a browser window).

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?

Input schema has zero parameters, establishing a baseline of 4. The description mentions '生まれ年から' (from birth year), which conceptually explains the required input despite the empty schema. Combined with the 'Browser-based tool' note, this clarifies that birth year input is handled through the interactive UI rather than function arguments, adding necessary semantic context.

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?

Description clearly states the tool calculates age, Japanese calendar era (和暦), zodiac (干支), constellation (星座), and school entrance/graduation years from birth year. The specific enumeration of Japanese cultural date systems clearly distinguishes it from sibling tool 'date-calculator'.

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 '(Browser-based tool)' annotation implies an interactive usage pattern where input is collected via browser UI rather than parameters, which provides implicit guidance. However, there is no explicit guidance on when to use this versus 'date-calculator' or other calendar tools, and no mention of prerequisites.

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 carries full burden. Adds valuable context that this is a 'Browser-based tool' (opens interactive UI) and clarifies the input→output flow (ad spend → metrics). However, lacks details on data persistence, rate limiting, or whether calculations are real-time vs cached.

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?

Extremely concise Japanese with arrow notation (→) efficiently mapping inputs to outputs. 'Browser-based tool' parenthetical adds execution context without verbosity. Every element earns its place with zero 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?

Adequate for a simple parameterless calculator. The input/output semantics are covered, though it relies on the tool name to establish Amazon context. No output schema exists, but the description enumerates return values (ACoS/ROAS/損益分岐CPC), which suffices for an interactive 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?

Zero parameters (empty schema) sets baseline to 4 per rubric. Description adds semantic context that the tool expects '広告費' (ad spend) as implicit input and produces ACoS/ROAS metrics, which explains the tool's function despite the empty parameter 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?

Specific verb '算出' (calculate) with clear resource types: ACoS, ROAS, and break-even CPC from ad spend. The metrics mentioned (ACoS/ROAS) inherently distinguish this from siblings like amazon-fba-calculator (fulfillment fees) and amazon-inventory-calculator (inventory levels).

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 specificity of advertising metrics implies usage for Amazon PPC/advertising analysis, but no explicit when-to-use guidance or named alternatives are provided. For example, it doesn't clarify when to use this vs amazon-keyword-extractor or cvr-improvement-checker.

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 behavioral disclosure burden. It mentions '(Browser-based tool)' indicating execution environment, but fails to explain interaction model (e.g., whether it opens an interactive UI, requires manual input, or returns calculated results). It also omits authentication requirements or data persistence 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?

Extremely efficient: formula notation (A+B+C→D) conveys calculation scope instantly, size classification feature is highlighted, and browser-based nature is noted parenthetically. Every element earns its place with zero 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?

For a zero-parameter tool with no output schema, the description adequately explains the calculation purpose. However, the 'Browser-based tool' annotation is cryptic—it should clarify whether this launches an external interface requiring user interaction or operates headlessly. Missing comparison guidance with 10+ sibling calculators.

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?

Input schema contains zero parameters (empty object), which establishes a baseline score of 4 per evaluation rules. The description appropriately makes no parameter claims since none exist, though it could have clarified why no parameters are needed (e.g., 'opens browser for manual 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?

Description clearly states the tool calculates FBA fees, storage fees, shipping fees, and profit, using specific domain terminology (サイズ区分/auto size classification). It distinguishes from generic calculators in the sibling list (e.g., base-fee-calculator, mercari-calculator) by explicitly naming Amazon FBA-specific cost components.

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?

While no explicit 'when-to-use' guidance is provided, the description strongly implies usage context through FBA-specific terminology (size classification, FBA fees) that differentiates it from sibling marketplace calculators. However, it does not explicitly contrast with alternatives like rakuten-fee-calculator or shopify-profit-calculator.

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 '(Browser-based tool)' annotation adds crucial behavioral context explaining the empty parameter schema, indicating the tool likely launches an interactive interface rather than accepting calculation inputs via parameters. However, lacking annotations, the description fails to disclose side effects, persistence, or whether it returns a URL vs launching a browser.

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?

Extremely efficient single-line description with formulaic notation (×, →) conveying the calculation logic compactly. No redundant words; every element serves a purpose.

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 zero-parameter schema and lack of output schema, the description minimally suffices by explaining the calculation purpose. However, it omits what the tool actually returns (calculation results? a URL? nothing?) and doesn't clarify the browser interaction model beyond the parenthetical hint.

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 zero parameters in the input schema, the baseline score is 4 per evaluation rules. The description mentions the conceptual inputs (purchase quantity, sales velocity) in the calculation formula, which helps explain why the schema is empty (values entered in browser UI), adding semantic value 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?

The description clearly identifies the calculation being performed (purchase quantity × sales velocity → appropriate inventory/reorder timing) using specific Japanese business terminology. It implicitly distinguishes from sibling tools like amazon-fba-calculator (fees) and amazon-acos-calculator (advertising) by focusing on inventory turnover math, though it could explicitly name relevant siblings.

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 select this tool versus similar Amazon calculators (amazon-fba-calculator, amazon-sales-dashboard) or other inventory tools. The description states what it calculates but not under what business conditions it should be invoked.

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 carries full burden. '(Browser-based tool)' hints at UI interaction but fails to disclose what triggers the browser, whether user interaction is required, output format, or side effects. Critical gap given the mutation/implication of scraping 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?

Single sentence efficiently conveys core function without redundancy. However, given the complexity (no parameters, browser-based implication), the extreme brevity underserves the agent's need for invocation context rather than demonstrating efficient information density.

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 0 parameters, no annotations, and no output schema, the description should compensate with rich behavioral context. Instead, it leaves critical gaps: how inputs are provided (description implies product names, schema has none), what 'browser-based' execution entails, and what the tool returns.

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?

While 0 parameters typically baseline at 4, the description creates confusion by stating keywords are extracted 'from product names' (商品名から) despite the empty input schema having no product_name field. This implicit expectation of input without schema support degrades clarity.

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?

Describes specific actions (分解・サジェスト生成/decompose and suggest) on specific resources (SEOキーワード from 商品名), clearly distinguishing from sibling calculators like amazon-fba-calculator. However, 'Browser-based tool' creates slight ambiguity about the execution model.

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 versus alternatives (e.g., when to use this versus amazon-acos-calculator or title-multilingual). No prerequisites or conditions mentioned despite the specialized Amazon SEO domain.

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 the use of localStorage for data persistence and identifies it as browser-based, which implies client-side operation. However, lacks critical behavioral details given no annotations: storage limits, data lifecycle (what happens on clear), whether it modifies existing data, or if it requires manual data entry versus API sync.

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?

Extremely concise single sentence. Information density is high with no waste. Minor deduction for the parenthetical '(Browser-based tool)' which feels appended rather than integrated, slightly disrupting flow.

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?

Adequately covers the core functionality (ASIN tracking, monthly charts, localStorage) for a parameterless tool, but lacks completeness for a dashboard tool: does not explain how data enters the system (manual input, import, API), export capabilities, or how it differs from the tracking/management siblings in the server.

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?

Input schema has zero parameters. With no parameters to describe, the baseline score of 4 applies. The description appropriately does not reference parameters since none exist.

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 manages Amazon sales, profit, and inventory data by ASIN using localStorage, and identifies it as a browser-based monthly graph dashboard. Distinguishes from sibling calculators by specifying localStorage persistence and ASIN-level granularity.

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 no explicit guidance on when to use this dashboard versus sibling tools like amazon-inventory-calculator or amazon-fba-calculator. Does not indicate prerequisites for data entry or importing.

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 of behavioral disclosure. It mentions 'Browser-based tool,' which hints at a user interface or web access, but does not describe key traits like whether it's read-only or mutative, authentication needs, rate limits, or output format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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 extremely concise and front-loaded: it states the core purpose in one clause and adds a brief technical note in parentheses. Every word earns its place, with no wasted sentences or redundant information, making it easy for an agent to parse quickly.

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 has 0 parameters, no output schema, and no annotations, the description is minimally adequate. It covers the basic purpose and a technical aspect ('Browser-based tool'), but lacks details on behavioral traits, usage context, or output expectations. For a tool with no structured data, it provides a foundation but leaves gaps that could hinder effective agent use.

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 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description does not need to add parameter semantics, and it appropriately avoids unnecessary details. A baseline of 4 is applied as it efficiently handles the lack of parameters without redundancy.

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: 'Accounts receivable/payable tracking with aging analysis.' It specifies the verb ('tracking') and resource ('accounts receivable/payable'), and adds a feature ('aging analysis'). However, it does not explicitly differentiate from sibling tools, as none appear to be direct alternatives for AR/AP management, though tools like 'balance-sheet' or 'profit-loss' might be related in financial contexts.

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 no guidance on when to use this tool versus alternatives. It mentions it is 'Browser-based tool,' which is a technical note but does not offer usage context, prerequisites, or exclusions. Without any when-to-use information, the agent must infer usage from the purpose alone.

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 carries full burden. It adds useful behavioral context by noting it is 'Browser-based' (execution environment) and includes templates (feature behavior), but omits details about data persistence, rate limits, auth requirements, or output format that would be necessary for safe invocation.

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?

Extremely compact single-line description using arrow notation (→) to efficiently convey the input-output flow. Every element (input type, output structure, feature, environment) earns its place with zero 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 zero schema parameters, no annotations, and no output schema, the description is insufficiently rich. It establishes core functionality but lacks output format details, sibling differentiation, or behavioral safety information needed to compensate for the absent structured metadata.

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?

Input schema is empty (0 parameters), establishing baseline 4. The description semantically clarifies that 'KW' (keyword) input is expected and processed, providing conceptual meaning even though no structured parameters are defined in 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 defines the transformation (KW input → H2/H3 heading structure proposal) and identifies the resource (article outlines). It specifies distinctive features (templates, browser-based) that differentiate it from generic content generators, though 'KW' abbreviation assumes SEO context without explicitly stating it.

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 provided on when to select this tool versus sibling content generators like 'meta-description-generator', 'comparison-table-generator', or 'nda-generator'. No prerequisites, constraints, or alternative selection criteria 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 provided, the description carries the full burden of behavioral disclosure. It states 'Create B/S', implying a write or generation operation, but doesn't clarify if this is a read-only simulation, a persistent creation, or what inputs are required (though parameters are zero). It mentions 'Browser-based tool', suggesting it might open a browser interface, but lacks details on permissions, side effects, or output format. For a tool with zero annotation coverage, this is insufficient.

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 and front-loaded: 'Create B/S from assets, liabilities, and equity. (Browser-based tool).' Both sentences earn their place—the first defines the core function, and the second adds crucial context about the execution environment. There is no wasted verbiage, making it highly 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 tool's complexity (financial statement generation), lack of annotations, no output schema, and zero parameters, the description is minimally complete. It states what the tool does and its browser-based nature, but doesn't explain the output (e.g., a generated document, data structure, or visual), behavioral traits, or how it differs from related financial tools. This is adequate for a simple tool but leaves gaps in understanding its full 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?

The input schema has 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't add parameter details, which is appropriate since there are none. It implies the tool uses 'assets, liabilities, and equity' as inputs, but these aren't formal parameters. Given zero parameters, a baseline of 4 is applied, as the description doesn't need to compensate for missing schema info.

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: 'Create B/S from assets, liabilities, and equity.' It specifies the verb ('Create') and resource ('B/S' meaning Balance Sheet), and distinguishes it from siblings like 'cash-flow-statement' and 'profit-loss' by focusing on balance sheet creation. However, it doesn't explicitly differentiate from 'trial-balance' or 'chart-of-accounts', which might be related financial tools, keeping it from a perfect score.

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 minimal usage guidance. It mentions 'Browser-based tool', which hints at the execution environment, but offers no explicit advice on when to use this tool versus alternatives like 'cash-flow-statement' or 'profit-loss'. There are no prerequisites, exclusions, or comparisons to sibling tools, leaving the agent with little context for 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool generates barcodes and is browser-based, but lacks details on output format (e.g., image type, size), permissions, rate limits, or error handling. For a tool with zero annotation coverage, this is insufficient to inform safe and effective use.

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 with two short phrases: 'Generate JAN, EAN, Code128 barcodes. (Browser-based tool).' Every word adds value—specifying barcode types and execution context—with no wasted text, making it front-loaded and 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 tool's simplicity (0 params, no output schema, no annotations), the description is incomplete. It lacks details on output (e.g., image format, download method), behavioral traits like rate limits, and usage context. For a generation tool, this leaves significant gaps in understanding how to invoke and interpret results effectively.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, which is appropriate. A baseline of 4 is applied as it meets the requirement for a parameterless tool without redundancy.

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: 'Generate JAN, EAN, Code128 barcodes.' It specifies the action (generate) and the resource (barcodes of specific types). However, it doesn't distinguish itself from potential siblings like 'qr-designer' or 'sku-generator' beyond mentioning barcode formats, which is a minor gap.

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 no guidance on when to use this tool versus alternatives. It mentions 'Browser-based tool,' which hints at execution context but doesn't clarify use cases, prerequisites, or comparisons with sibling tools like 'qr-designer' for different code types. This leaves the agent without explicit usage direction.

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 for behavioral disclosure. While 'encode/decode' implies transformation operations, the description doesn't mention error handling, performance characteristics, limitations (e.g., file size constraints), or what happens with invalid input. For a tool with no annotation coverage, this represents significant gaps in behavioral transparency.

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 (5 words) and front-loaded with the core functionality. Every word earns its place with zero waste, making it easy for an agent to quickly understand the tool's purpose.

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 relatively simple transformation tool with good schema coverage but no annotations and no output schema, the description provides minimal but adequate context about what the tool does. However, it lacks important details about behavioral characteristics and usage guidelines that would make it more complete for agent invocation.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description mentions 'text and files' which somewhat expands on the 'text' parameter's scope, but doesn't add meaningful semantic context beyond what the schema provides. The baseline score of 3 is appropriate when the schema does the heavy lifting.

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 function with specific verbs ('encode/decode') and resources ('text and files to Base64'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools, which appear to be unrelated utilities rather than competing Base64 converters, so sibling differentiation isn't applicable here.

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 no guidance on when to use this tool versus alternatives, prerequisites, or contextual considerations. It simply states what the tool does without any usage context, leaving the agent to infer appropriate scenarios.

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 carries the full burden. It successfully discloses the browser-based nature of the tool (important for agent expectation management) and specifies the calculation logic (3% service fee + payment fees). It stops short of explaining side effects, persistence, or exact return behavior, but covers the essential 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?

Extremely efficient: 'サービス利用料3%+決済手数料→利益計算' defines the calculation logic, 'スタンダード/グロース比較' identifies the comparison feature, and '(Browser-based tool)' indicates the modality. No wasted words, front-loaded with core functionality.

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 calculator tool without output schema, the description is sufficiently complete. It identifies the platform (BASE), fee structure, and browser-based delivery method. It could optionally clarify that no input parameters are required, though this is evident from 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?

Input schema contains zero parameters. Per rubric, this establishes a baseline of 4. The description appropriately makes no mention of parameters (which would be confusing given the empty schema), maintaining consistency with the schema definition.

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?

Description clearly states the tool calculates BASE platform fees (3% service fee + payment processing fee) for profit calculation and compares Standard vs Growth plans. The specific platform name (BASE) and fee structure distinguish it from sibling calculators like rakuten-fee-calculator and amazon-fba-calculator.

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?

While the platform-specific name and 'Standard/Growth comparison' implicitly suggest use for BASE fee analysis, there is no explicit guidance on when to select this over the numerous sibling fee calculators (e.g., mercari-calculator, shopify-profit-calculator) or prerequisites for 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 provided, the description carries full burden but only adds 'Browser-based tool' as behavioral context. It lacks crucial details: whether it's read-only or destructive, authentication needs, rate limits, output format, or processing time. For a zero-parameter AI tool, this leaves significant behavioral gaps.

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?

Extremely concise with two brief phrases that each add value: the first states the core function and scope, the second provides implementation context. No wasted words, perfectly front-loaded with the primary purpose.

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 tool with no output schema and no annotations, the description is incomplete. It doesn't explain what happens after clicking (e.g., file upload interface, output format, success/failure behavior). The 'Browser-based tool' hint helps but doesn't compensate for missing operational details.

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 zero parameters with 100% schema description coverage, so the schema already fully documents the input interface. The description appropriately doesn't add parameter details, maintaining focus on the tool's purpose rather than redundant information.

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 function as 'One-click AI background removal' with specific targets (people, products, objects), which goes beyond just restating the name/title. However, it doesn't explicitly differentiate from sibling tools like 'pro-matting' or 'image-crop' that might have overlapping functionality.

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 minimal guidance with 'Browser-based tool' hinting at context, but offers no explicit when-to-use advice, prerequisites, or alternatives. It doesn't help an agent decide between this and similar sibling tools like 'pro-matting' or 'image-crop'.

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 of behavioral disclosure. It states the tool is a 'calculator,' implying a read-only, computational function without side effects, but does not explicitly confirm this or detail any behavioral traits like error handling, performance limits, or output format. For a tool with no annotations, this is a significant gap in transparency.

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 with a single sentence: 'Yield to maturity, duration, and convexity calculator.' It is front-loaded and wastes no words, making it easy to parse quickly. Every part of the sentence directly contributes to understanding the tool's purpose.

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 (7 parameters, financial calculations) and lack of annotations and output schema, the description is insufficient. It does not explain the relationship between inputs and outputs, error conditions, or practical usage examples. For a calculator with multiple modes and parameters, more context is needed to guide effective use.

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 description does not add any parameter-specific information beyond what the input schema provides. Since schema description coverage is 100%, the baseline score is 3. The description's mention of 'yield to maturity, duration, and convexity' hints at outputs but does not clarify input semantics, such as how parameters like 'calcMode' affect calculations, so it adds no extra 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 the tool's purpose as a calculator for 'yield to maturity, duration, and convexity,' which are specific financial metrics for bonds. It uses the verb 'calculator' with the resource 'bond yield' implied in the name, making the function unambiguous. However, it does not explicitly differentiate from sibling tools like 'npv-irr-calc' or 'investment-simulator,' which might also involve financial calculations, so it misses full sibling distinction.

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 no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, context, or exclusions, such as when to choose this over other financial calculators in the sibling list. The lack of usage context leaves the agent without direction on appropriate scenarios for 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool is browser-based, which adds some context about the execution environment, but fails to describe output format, whether it requires user input, or any limitations (e.g., data persistence, privacy). This leaves significant gaps for a tool that likely generates documents.

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 short phrases that are front-loaded with the core functionality. Every word earns its place, with no redundant or vague language.

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 has 0 parameters and no output schema, the description is minimally adequate. It covers the basic purpose and execution context, but as a document-generation tool with no annotations, it should ideally specify output types or usage constraints to be fully 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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by specifying '3 format styles' and 'browser-based', which provides context beyond the empty schema, though it doesn't detail what those formats are.

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 professional CV in 3 format styles, specifying both the resource (CV) and the action (generate). It distinguishes from siblings like 'resume-generator' by mentioning format styles, though it could be more explicit about the difference.

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 alternatives like 'resume-generator' or other career-related tools. The description mentions it's browser-based, which is a minor contextual hint, but lacks explicit usage scenarios or 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 are provided, so the description carries full burden. It states the tool is 'browser-based', which hints at execution environment but doesn't disclose key behavioral traits like whether it requires user input, how it generates the statement, if it's read-only or creates outputs, or any limitations. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operation.

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 very brief—two short phrases—with no wasted words. It's front-loaded with the core purpose. However, it could be slightly more informative without losing conciseness, such as clarifying what 'indirect method' entails or the output format.

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 annotations, no output schema, and a tool that likely produces a financial statement (a non-trivial output), the description is incomplete. It doesn't explain what the tool returns, how it operates, or any dependencies. For a generation tool with zero structured context, this leaves too many unanswered questions for effective use.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, which is appropriate here. Baseline is 4 for 0 parameters, as the schema fully covers the absence of inputs.

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 it's for 'cash flow statement generation' using the 'indirect method', which clarifies the verb (generate) and resource (cash flow statement) with a specific method. However, it doesn't distinguish from sibling tools like 'balance-sheet' or 'profit-loss' beyond the different financial statement type, leaving some ambiguity about its unique scope compared to other financial 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?

No guidance is provided on when to use this tool versus alternatives. The description mentions it's 'browser-based', but this doesn't help differentiate it from other tools or indicate specific contexts or prerequisites for use. There's no mention of when-not-to-use or comparisons to similar financial 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 the full burden of behavioral disclosure. It mentions 'Browser-based tool', indicating it likely opens a browser interface, but doesn't cover critical aspects like whether it creates permanent outputs, requires authentication, has rate limits, or what happens after execution. For a tool with potential file generation, this is a significant gap.

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 brief phrases that directly state the tool's function and execution context. Every word earns its place, with no redundancy or fluff, making it easy to parse quickly.

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 (likely involves document generation) and lack of annotations or output schema, the description is minimally adequate. It covers the core purpose and execution method but omits details on outputs, errors, or behavioral traits. For a zero-parameter tool, it meets basic needs but leaves gaps for informed use.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by hinting at functionality ('templates and name mail-merge'), which suggests internal options or UI elements, though it doesn't detail them. Baseline is 4 for zero parameters, as the description provides some context beyond the empty 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 the tool's purpose as 'Award certificates with templates and name mail-merge', specifying the action (award), resource (certificates), and key features (templates, mail-merge). It distinguishes itself from siblings like 'resume-generator' or 'contract-generator' by focusing on certificates, though it doesn't explicitly differentiate from similar document-generation 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?

No guidance is provided on when to use this tool versus alternatives. The description mentions it's 'Browser-based', which hints at a UI context, but doesn't specify prerequisites, ideal scenarios, or exclusions. Without this, users must infer usage from the purpose alone.

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?

Without annotations, the description carries the full disclosure burden. It adds valuable context by labeling itself 'Browser-based tool' (indicating client-side execution/UI interaction), but fails to specify output format details, input size constraints, or whether the output is copied to clipboard vs returned as text.

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

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

Extremely efficient: input→output format logic with a parenthetical implementation detail. Every element earns its place; no redundancy. The arrow notation effectively conveys the transformation in minimal space.

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 formatting utility with no output schema, the description covers the core purpose but remains incomplete. It should specify the exact YouTube chapter syntax (e.g., '00:00 Title') and clarify how the browser-based interaction works (opens input dialog? requires manual paste?).

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 zero parameters, baseline is 4 per scoring rules. The description adds necessary semantic context by describing what input the tool expects ('動画の区切り') even though it is not provided via parameters, clarifying the tool's interactive nature.

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 transformation workflow (video segments → YouTube chapter format) using specific terminology. However, it could better distinguish from `timestamp-generator` and `video-duration-calculator` by explicitly mentioning it formats timestamps with titles into the specific 00:00 syntax used by YouTube.

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?

While the arrow notation implies a workflow, there is no explicit guidance on when to use this versus siblings like `youtube-description-generator` or `timestamp-generator`. It does not state prerequisites (e.g., having timestamp data ready) or that it is an interactive browser tool versus API-style.

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 carries the full burden of behavioral disclosure. It mentions 'search and custom additions', hinting at read and write capabilities, but doesn't clarify permissions, data persistence, or side effects. The 'Browser-based tool' note adds implementation detail but not operational behavior, leaving significant gaps for a tool that likely modifies financial data.

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 brief and front-loaded with the core functionality ('100+ standard accounts with search and custom additions'), though the parenthetical note adds minor clutter. It avoids redundancy and stays focused, but could be slightly more polished by integrating the browser note more seamlessly.

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 complexity of financial account management, no annotations, and no output schema, the description is insufficient. It lacks details on what the tool returns, how 'search' and 'custom additions' work, error conditions, or integration with sibling tools, making it incomplete for safe and effective use.

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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't discuss parameters, which is appropriate here, earning a baseline score of 4 for not introducing unnecessary information.

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 '100+ standard accounts with search and custom additions' vaguely indicates a tool for managing a chart of accounts, but lacks a specific verb (e.g., 'view', 'manage', 'edit') and doesn't clearly distinguish it from sibling tools like 'balance-sheet' or 'trial-balance'. The parenthetical '(Browser-based tool)' adds technical context but not functional 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 alternatives like 'balance-sheet' or 'journal-entry'. The description implies it handles accounts, but doesn't specify use cases, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

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 action ('Check') but doesn't disclose behavioral traits like authentication needs, rate limits, error conditions, or what the output might contain. For a tool that likely interacts with external services (Stripe), this is a significant gap in transparency.

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, efficient sentence with zero waste. It's front-loaded with the core purpose and avoids unnecessary elaboration, making it easy to parse quickly.

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 tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'status' entails (e.g., active, canceled, pending), the format of the response, or any dependencies on external systems like Stripe. This leaves critical gaps for an agent to use the tool effectively.

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 description coverage is 100%, with the single parameter 'session_id' well-documented in the schema as 'Stripe checkout session ID (cs_xxx)'. The description adds no additional parameter semantics beyond what the schema provides, so the 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 verb ('Check') and resource ('status of a JobDoneBot checkout session'), making the purpose specific and understandable. However, it doesn't distinguish this tool from potential siblings like 'subscribe-pro' or other subscription-related tools, which could cause confusion in a crowded toolset.

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 no guidance on when to use this tool versus alternatives, prerequisites, or context. Given the many sibling tools (e.g., 'subscribe-pro'), this lack of differentiation leaves the agent guessing about appropriate 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the browser-based nature and chime sounds, but doesn't cover important aspects like whether it requires user interaction, how the timer is controlled, what happens when it completes, or any limitations (e.g., maximum duration, sound options). For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 just two phrases, with zero wasted words. It's front-loaded with the core functionality ('full-screen countdown timer with chime sounds') followed by implementation context ('browser-based tool'). Every element 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?

For a zero-parameter tool with no output schema, the description provides basic purpose and implementation context. However, without annotations and given the behavioral gaps mentioned, it's only minimally adequate. The agent knows what the tool does at a high level but lacks important operational details.

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 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose and behavior. Baseline for 0 parameters is 4.

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 function as a 'full-screen countdown timer with chime sounds' and specifies it's 'browser-based', which provides specific verb+resource+environment context. However, it doesn't differentiate from the sibling 'countdown-timer' tool, which appears to serve a similar purpose.

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 about when to use this tool versus alternatives. The description doesn't mention any specific use cases, prerequisites, or comparisons with the sibling 'countdown-timer' tool, leaving the agent without contextual usage direction.

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 carries full behavioral burden but fails to disclose error handling (what happens on invalid syntax), whether output is returned as string or file, or the read-only/transformative nature of the operation beyond the implied 'format' verb.

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 zero waste. Front-loaded with action ('Format source code') and immediately qualifies scope (engine + languages). 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?

Lacks output schema and annotations, yet description fails to explain return values, error states, or success behavior. For an 8-parameter transformation tool, the absence of output documentation creates a significant gap in agent understanding.

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%, establishing baseline 3. Description adds 'Prettier' context which helps frame the style options (semi, trailingComma) and lists supported languages matching the enum, but adds no specific syntax guidance or parameter relationships beyond schema 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?

States specific verb (Format) + resource (source code) + engine (Prettier) and lists supported languages. Implicitly distinguishes from sibling 'sql-formatter' by omitting SQL and from 'format-converter' by specifying Prettier/source code, though lacks explicit comparative guidance.

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 no guidance on when to select this tool versus siblings like 'sql-formatter' (SQL formatting) or 'format-converter' (file conversion), nor mentions prerequisites like valid syntax requirements.

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 mentions 'カラーピッカー付き' (with color picker), hinting at additional functionality, but doesn't disclose behavioral traits like whether it's read-only, requires authentication, has rate limits, or what the output looks like. For a conversion tool with zero annotation coverage, this is inadequate.

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?

Extremely concise with two brief phrases: 'HEX・RGB・HSL・CMYKを相互変換' and 'カラーピッカー付き'. Every word earns its place, and the purpose is front-loaded. No wasted sentences.

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 annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., converted values, error handling), behavioral constraints, or usage context. For a tool with two parameters and conversion logic, more detail is needed to guide an AI agent effectively.

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

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

Schema description coverage is 100%, so the schema fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema. It implies conversion between formats but doesn't explain parameter interactions or provide examples beyond the schema's examples. Baseline 3 is appropriate when schema does the heavy lifting.

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 function: 'HEX・RGB・HSL・CMYKを相互変換' (mutual conversion between HEX, RGB, HSL, CMYK formats). It specifies the verb (convert) and resources (color formats). However, it doesn't explicitly distinguish from sibling tools like 'color-palette' or 'image-color-picker' beyond mentioning 'カラーピッカー付き' (with color picker).

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 alternatives. The description doesn't mention sibling tools or contextual usage scenarios. It lacks prerequisites, exclusions, or comparisons to similar tools in the list.

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 carries the full burden of behavioral disclosure. It mentions 'browser-based tool,' which hints at client-side execution but doesn't clarify key traits like whether it's deterministic, if it requires internet access, what the output format is (e.g., HEX codes, RGB values), or any limitations (e.g., number of colors per palette). This leaves significant gaps for an AI agent to understand how to invoke it effectively.

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 brief phrases that directly state the tool's function and context. Every word earns its place: 'Generate harmonious color palettes' defines the action, 'for design projects' provides usage context, and '(Browser-based tool)' adds implementation detail. No wasted sentences or 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 (0 parameters, no annotations, no output schema), the description is minimally adequate. It covers the basic purpose and hints at execution environment but lacks details on output format, behavioral constraints, or integration guidelines. For a tool with no structured data to rely on, it should do more to be fully helpful, but it meets the bare minimum for a zero-parameter 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here. A baseline of 4 is given since the schema fully handles parameters, and the description doesn't need to compensate—it focuses on the tool's purpose instead.

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 with a specific verb ('Generate') and resource ('harmonious color palettes'), and provides context ('for design projects'). It distinguishes from siblings like 'color-converter' or 'image-color-picker' by focusing on palette generation rather than conversion or extraction. However, it doesn't explicitly differentiate from all possible palette-related tools, keeping it at a 4 rather than a 5.

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

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

The description provides minimal usage guidance—only that it's for design projects and browser-based. It doesn't specify when to use this tool versus alternatives (e.g., 'color-converter' for single colors, 'image-color-picker' for extracting from images) or any prerequisites. No explicit when/when-not instructions are given, making it inadequate for informed 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?

With no annotations provided, the description carries the full burden and discloses key behavioral traits: performance ('30秒で' - 30 seconds) and execution environment ('Browser-based tool'). However, it omits details about data persistence, offline capability, or output limitations that would be valuable for a zero-parameter 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?

Extremely efficient two-sentence structure with zero waste. The first sentence covers function and speed; the second covers integration workflow and technical context. Information is front-loaded with the core value proposition (HTML generation).

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 (zero parameters) and lack of output schema, the description adequately covers the essential context: output format (HTML), usage workflow (copy-paste), and performance expectations. It sufficiently enables an agent to recommend this tool for WordPress content creation scenarios.

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 zero parameters, which per the rubric establishes a baseline of 4. The description appropriately makes no parameter claims since the tool appears to work without inputs or uses an internal wizard, matching the empty schema 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 uses specific action '生成' (generate) with clear resource '商品比較表HTML' (product comparison table HTML). It effectively distinguishes from sibling generators like 'article-outline-generator' or 'contract-generator' by specifying the exact output type (comparison tables) and target platform (WP/WordPress).

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 phrase 'コピペでWPに貼れる' implies the intended use case (creating content for WordPress paste), providing implicit context. However, it lacks explicit guidance on when NOT to use this versus other table tools or prerequisites for 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?

No annotations are provided, so the description carries full burden. It mentions 'Browser-based tool', hinting at UI interaction, but fails to disclose critical behaviors like whether it creates editable documents, requires authentication, has rate limits, or handles errors. This leaves significant gaps for a generation 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?

The description is extremely concise with two short phrases, front-loading the core purpose ('Generate business contracts from templates') and adding a brief note on implementation ('Browser-based tool'). Every word serves a purpose 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?

For a tool with no annotations, no output schema, and 0 parameters, the description is incomplete. It lacks details on output format (e.g., PDF, editable document), error handling, template sources, or any behavioral traits needed for effective use in a business 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?

With 0 parameters and 100% schema coverage, the baseline is 4. The description doesn't need to add parameter details, but it implies templates are involved without specifying how they're selected or customized, which is a minor gap given the zero-param context.

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 'Generate business contracts from templates' clearly states the tool's action (generate) and resource (business contracts), but it's vague about scope and templates. It doesn't distinguish from siblings like 'nda-generator' or 'terms-generator', which might serve similar legal document purposes.

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 like 'nda-generator' or 'terms-generator' is provided. The description lacks context about prerequisites, such as needing templates or specific business contexts, offering no usage differentiation.

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 carries the full burden of behavioral disclosure. It adds 'リアルタイム' (real-time) and 'Browser-based tool' which hint at the operational nature, but fails to specify whether it returns structured data, opens a browser window, or requires user interaction, leaving significant ambiguity for agent invocation.

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 compact with zero redundancy: a question establishing the use case followed by a two-word functional label and parenthetical technical note. Every component earns its place without 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?

Given the absence of an output schema and annotations, the description should ideally disclose what the tool returns (e.g., days remaining, a visual timer, or a browser URL). While it mentions the browser-based nature, it leaves the actual output format and side effects unspecified, creating a gap 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?

The input schema contains zero parameters, establishing a baseline score of 4. The description appropriately does not invent parameter documentation where none exists, matching the schema 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 clearly identifies the tool's function (countdown to specific dates/holidays) using concrete examples (Christmas, New Year, Golden Week). It distinguishes from siblings like classroom-timer and timezone-converter by focusing on holiday/event countdowns rather than general timing or conversion tasks.

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 scenarios through the listed holiday examples (Christmas, New Year, GW), giving users context for when to invoke this tool. However, it lacks explicit guidance on when not to use it or alternatives for custom date countdowns.

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 carries full burden but reveals little. 'Visually' hints at a user-friendly interface, but doesn't disclose behavioral traits like whether it's read-only vs. mutating, authentication needs, rate limits, error handling, or what 'visually' entails. For a tool with zero annotation coverage, this is insufficient.

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?

Extremely concise with a single, front-loaded sentence that wastes no words. Every word ('Build', 'parse', 'cron expressions', 'visually') contributes directly to understanding the tool's core functionality.

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 annotations, no output schema, and a tool that likely produces visual or descriptive output, the description is incomplete. It doesn't explain what 'visually' means (e.g., graphical interface, human-readable description), what the output looks like, or any constraints. For a tool with dual modes and visual output, this lacks necessary 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 description coverage is 100%, so the schema already documents both parameters ('mode' with enum values, 'expression' with format). The description adds no parameter-specific details beyond what's in the schema, such as examples of valid expressions or visual output format. Baseline 3 is appropriate when schema does the heavy lifting.

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 'Build and parse cron expressions visually' clearly states the tool's dual functionality with specific verbs ('build', 'parse') and resource ('cron expressions'). It distinguishes from most siblings by focusing on cron expressions, though it doesn't explicitly differentiate from potential similar tools like 'timestamp-converter' or 'date-calculator'.

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 alternatives. The description doesn't mention prerequisites, typical use cases, or when to choose 'parse' vs 'generate' mode. It's a generic statement that offers no contextual decision-making help.

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 of behavioral disclosure. It mentions the conversion happens 'in the browser', which adds some context about the execution environment. However, it lacks details on permissions, rate limits, error handling, or what the output looks like (e.g., format of returned data). For a tool with no annotations, this is insufficient.

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, efficient sentence that front-loads the core functionality. There's no wasted text, and it's appropriately sized for the tool's complexity. Every word earns its place by clearly stating the conversion purpose and context.

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 moderate complexity (5 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits, output format, or usage guidelines. With no output schema, it should ideally hint at return values, but the schema's high coverage mitigates some gaps, making it just viable.

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%, meaning all parameters are documented in the schema. The description doesn't add any parameter-specific details beyond what's in the schema (e.g., it doesn't explain the 'direction' parameter's implications or provide examples). With high schema coverage, the baseline is 3, as the description doesn't compensate with extra semantic value.

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: converting between CSV and Excel formats in the browser. It specifies the verb 'convert' and resources 'CSV and Excel (.xlsx)', making the function unambiguous. However, it doesn't differentiate from sibling tools like 'json-to-csv' or 'format-converter', which might handle similar conversions, so it doesn't reach a perfect score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'json-to-csv' or 'format-converter', nor does it specify prerequisites or exclusions. The usage is implied by the name and description, but no explicit context is 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 provided, the description carries full burden but offers minimal behavioral insight. It mentions 'SQL-like queries' but doesn't disclose critical traits like whether this is a read-only operation, error handling, performance constraints, or output format. For a tool that processes data, this leaves significant gaps in understanding its 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 extremely concise—a single sentence with zero wasted words. It's front-loaded with the core functionality ('Run SQL-like queries on CSV data'), making it easy to parse quickly.

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 (querying data), lack of annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., results, errors), behavioral constraints, or usage context, leaving the agent with inadequate information to use it effectively.

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

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

Schema description coverage is 100%, so the schema already documents both parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., CSV format details or query syntax examples), meeting the baseline for high 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?

The description clearly states the tool's purpose with a specific verb ('Run') and resource ('CSV data'), making it immediately understandable. However, it doesn't distinguish this tool from potential siblings like 'csv-excel-converter' or 'json-to-csv' that also handle CSV data but with different operations.

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 about when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., CSV format requirements), limitations (e.g., query complexity), or related tools (e.g., 'csv-excel-converter' for format conversion instead of querying).

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 carries the full burden of behavioral disclosure. It identifies the browser-based nature of the tool, which explains the empty parameter schema, but fails to disclose what data sources it accesses, privacy implications of analyzing content, or the format of improvement suggestions returned.

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 two-sentence Japanese description is tightly constructed with no wasted words. The first sentence covers analysis targets and the second covers output deliverables, with the parenthetical browser notation earning its place by explaining the parameter-less schema.

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 tool without output schema, the description adequately covers the core functionality. However, it lacks critical contextual details such as how the article content is provided (context, clipboard, URL?), expected processing time, or the nature of the browser interaction, leaving gaps in the agent's ability to predict execution behavior.

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 contains zero parameters, which per evaluation rules establishes a baseline score of 4. The description implicitly explains why the schema is empty (browser-based tool handles inputs separately), providing adequate semantic context for the parameter 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 uses specific verbs (分析, 提示) and resources (CTA配置, リンク密度, 読了率) to clearly define the tool's focus on conversion rate optimization for articles. It distinguishes from siblings like article-outline-generator (creation) and sales-writing-analyzer (general analysis) through specific metrics mentioned.

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?

While the '(Browser-based tool)' notation hints at the execution mechanism, the description provides no explicit guidance on when to use this tool versus similar alternatives like sales-writing-analyzer or rewrite-assistant, nor does it mention prerequisites such as requiring article content or URLs.

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 of behavioral disclosure. It mentions output formats (JSON/CSV) but does not cover critical aspects like rate limits, authentication requirements, error handling, or whether the operation is idempotent. For a data generation tool with no annotation coverage, this leaves significant gaps in understanding its 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 extremely concise and front-loaded, consisting of a single sentence that directly states the tool's purpose and output formats. There is no wasted language, and every word contributes to understanding the tool's function.

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 moderate complexity (4 parameters, no output schema, and no annotations), the description is minimally adequate. It covers the basic purpose and output formats but lacks details on behavioral traits, usage guidelines, and parameter nuances. The high schema description coverage helps, but the overall context remains incomplete for effective tool selection and 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?

The description does not add any parameter-specific information beyond what is already in the input schema, which has 100% description coverage. It mentions the types of data generated (e.g., names, emails, addresses), which loosely relates to the 'fields' parameter but does not provide additional semantics or usage examples. The baseline score of 3 is appropriate given the high 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?

The description clearly states the tool's purpose: 'Generate realistic fake data (names, emails, addresses) in JSON/CSV.' It specifies the verb ('Generate'), resource ('realistic fake data'), and output formats. However, it does not explicitly differentiate from sibling tools, as none appear to be direct alternatives for fake data generation.

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 no guidance on when to use this tool versus alternatives. It lacks context about prerequisites, typical use cases, or comparisons with other tools. Without such information, the agent must infer usage based solely on the tool's name and description.

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 of behavioral disclosure. It lists operations but doesn't specify input formats (though the schema covers this), error handling, timezone handling, or output structure. For a tool with multiple modes and no annotations, this leaves significant behavioral gaps.

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—a single sentence with three comma-separated clauses—and front-loaded with all key operations. Every word earns its place, with no redundant or vague phrasing.

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 moderate complexity (5 parameters, 3 modes), 100% schema coverage, and no output schema, the description is minimally adequate. It lists operations but lacks details on output format, error cases, or behavioral nuances. Without annotations or output schema, more context would be helpful for effective use.

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

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

Schema description coverage is 100%, so the schema fully documents all parameters. The description mentions 'date differences', 'add/subtract dates', and 'count business days', which loosely map to the 'mode' parameter values ('diff', 'add', 'business-days'), but adds no additional semantic context beyond what the schema provides. This meets the baseline for high 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?

The description clearly states the tool's purpose with specific verbs ('calculate', 'add/subtract', 'count') and resources ('date differences', 'dates', 'business days'). It distinguishes itself from siblings like 'age-calculator' and 'timestamp-converter' by focusing on date arithmetic rather than age calculation or timestamp conversion, though it doesn't explicitly differentiate from them.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, exclusions, or compare it to sibling tools like 'age-calculator' or 'timestamp-converter', leaving the agent to infer usage context solely from the tool name and description.

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 mentions 'Browser-based tool,' indicating it runs in a browser context, which is useful. However, it lacks details on permissions, side effects (e.g., whether it saves or downloads files), rate limits, or output format. For a generation tool with zero annotation coverage, this leaves significant behavioral gaps.

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 brief and front-loaded with the main purpose, but the second part 'Browser-based tool' feels tacked on without clear necessity. It's concise but could be more structured to integrate the context seamlessly, earning a mid-range score for minimal waste but room for improvement.

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 zero parameters and no output schema, the description is moderately complete. It states what the tool does and adds browser context, but as a generation tool with no annotations, it should ideally mention output behavior (e.g., file download, preview). It's adequate but has gaps in behavioral transparency.

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 0 parameters with 100% schema description coverage, so the schema fully documents inputs. The description adds no parameter information, which is acceptable here. Baseline is 4 for zero parameters, as there's nothing to compensate for, and the schema suffices.

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: 'Generate delivery notes with receipt confirmation field.' It specifies the verb ('Generate'), resource ('delivery notes'), and a key feature ('receipt confirmation field'). However, it doesn't differentiate from sibling tools like 'invoice-generator' or 'receipt-generator' that might overlap in document generation contexts.

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 no guidance on when to use this tool versus alternatives. It mentions 'Browser-based tool,' which hints at the execution environment but doesn't clarify use cases, prerequisites, or comparisons to siblings like 'invoice-generator' or 'purchase-order' that might serve similar business documentation needs.

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 of behavioral disclosure. It mentions the calculation methods but does not describe output format (e.g., schedule structure, time periods), error handling, or computational limits. For a tool with no annotations, this leaves significant gaps in understanding how it behaves.

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—a single phrase that directly states the tool's core functionality with zero redundant words. It is front-loaded and efficiently communicates the essential purpose without unnecessary elaboration.

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 (financial calculations with 6 parameters) and lack of annotations or output schema, the description is insufficient. It does not explain the output format, error conditions, or provide examples, making it hard for an agent to use correctly without trial and error.

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

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

Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional parameter semantics beyond what the schema provides, such as explaining relationships between parameters (e.g., how method affects calculations) or typical values. This meets the baseline for high 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?

The description clearly states the tool's purpose: generating depreciation schedules using straight-line and declining-balance methods. It specifies the verb ('depreciation schedules') and resource (implied financial calculations), but does not differentiate from sibling tools like 'npv-irr-calc' or 'bond-yield-calc' which are also financial calculators, leaving some ambiguity about when to choose this specific 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 provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, typical use cases, or compare it to sibling financial calculation tools, leaving the agent with no context for tool selection beyond the name and description.

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 of behavioral disclosure. It mentions 'side-by-side' comparison, implying a visual or structured output, but doesn't detail aspects like performance limits, error handling, or output format specifics beyond what the schema covers. For a tool with no annotations, this leaves significant behavioral gaps.

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 and front-loaded, consisting of a single, clear phrase: 'Side-by-side text and code diff comparison.' Every word earns its place by conveying the core functionality without unnecessary elaboration, making it efficient for quick understanding.

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 moderate complexity (5 parameters, no output schema, no annotations), the description is minimally adequate. It states the purpose but lacks details on output behavior, error cases, or integration context. Without annotations or an output schema, the description doesn't fully compensate for these gaps, making it just sufficient for basic use.

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 description coverage is 100%, with all parameters well-documented in the schema itself. The description adds no additional meaning beyond the schema, such as explaining the significance of 'left' vs 'right' or use cases for different formats. Since the schema does the heavy lifting, the 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: 'Side-by-side text and code diff comparison.' It specifies the verb ('diff comparison') and resource ('text and code'), making it understandable. However, it doesn't explicitly differentiate from sibling tools like 'similarity-checker' or 'code-formatter', which might have overlapping functions, preventing a perfect score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention any specific contexts, prerequisites, or exclusions, such as comparing file types or handling large inputs. With many sibling tools present, including 'similarity-checker', the lack of differentiation leaves the agent without clear usage cues.

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 disclosure burden. It adds value by noting this is a 'Browser-based tool', explaining the empty parameter schema (interactive UI expected). However, it omits mutation safety, authentication requirements, or data persistence details that annotations would typically cover.

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 efficient sentence front-loaded with the core value proposition (profit comparison). The parenthetical '(Browser-based tool)' is slightly abrupt but provides essential context for the empty parameter schema without excessive verbosity.

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 zero parameters and no output schema, the description adequately covers the tool's purpose but leaves interaction ambiguity (how users input product details if not via parameters). For a tool with numerous sibling calculators, it should explicitly clarify why this comparison tool versus specific calculators.

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 contains zero parameters. Per evaluation rules, 0 parameters establishes a baseline score of 4. The description does not add input semantics, but none are required given the schema state.

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 compares profits when selling the same product across various EC platforms (各ECで売った場合の利益を一覧比較), using specific verbs (比較) and scope. It implicitly distinguishes from single-platform calculators like amazon-fba-calculator via 'various EC platforms', though it does not explicitly contrast with sibling alternatives.

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 no explicit guidance on when to use this comparative tool versus specific platform fee calculators (e.g., mercari-calculator, rakuten-fee-calculator) or what prerequisites exist. The user must infer usage solely from the purpose statement.

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 disclosure burden. The parenthetical '(Browser-based tool)' hints at execution context but does not explain output format, side effects, whether it creates persistent resources, or required authentication. For a mutation/content-generation tool with zero annotation coverage, this is insufficient behavioral 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 appropriately compact as a single sentence with the core value proposition front-loaded. The parenthetical '(Browser-based tool)' at the end is slightly cryptic (unclear if it refers to execution environment or target platform type) but does not significantly detract from readability.

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 zero parameters and no output schema, the description explains what content is generated (platform-specific templates for three scenarios) but leaves critical invocation context ambiguous. Without parameters to guide the AI on which specific template to generate (purchase vs shipping vs returns) or platform selection, the description is incomplete regarding how the tool determines what to output.

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 contains zero parameters. Per the evaluation rules, zero parameters warrants a baseline score of 4. There are no parameters requiring semantic elaboration beyond what the empty schema conveys.

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 specifies the tool generates fixed phrases (定型文) for specific EC scenarios: purchase thank-you notes, shipping notifications, and return handling. It also mentions platform-specific generation (プラットフォーム別), distinguishing it from siblings like review-reply-template. However, it could clarify what 'platform' means (e.g., Amazon, Shopify) given the presence of specific platform calculators in siblings.

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 guidelines are provided for when to use this tool versus alternatives like review-reply-template or product-description-generator. While the three use cases (purchase/shipping/returns) imply the scope, there is no guidance on selection criteria, prerequisites, or when NOT 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 carries full burden. It mentions 'Browser-based tool', which hints at execution environment, but lacks critical behavioral details: how PDFs are processed (e.g., upload method, supported formats), whether data is stored or transient, error handling, or output format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its operation.

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: one sentence in Japanese followed by a brief English note. It's front-loaded with the main function and wastes no words. Every part ('見積書PDFから経費明細表を自動生成' and 'Browser-based tool') adds value without 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 tool's complexity (PDF processing with no parameters) and lack of annotations/output schema, the description is minimally adequate. It states what the tool does and the execution context, but lacks details on input handling (e.g., PDF requirements), output specifics, or error conditions. Without structured fields to rely on, it leaves the agent with incomplete operational 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?

The tool has 0 parameters with 100% schema description coverage (empty schema). The description doesn't need to explain parameters, as there are none. It appropriately focuses on the tool's core function without redundant parameter details, meeting the baseline for zero-parameter tools.

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: '見積書PDFから経費明細表を自動生成' (automatically generate expense details from estimate PDF). It specifies the verb (generate), resource (estimate PDF), and output (expense details table). However, it doesn't distinguish from siblings like 'expense-report' or 'receipt-generator', which might handle similar financial documents.

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 minimal usage guidance. It mentions 'Browser-based tool', implying it runs in a browser context, but offers no explicit when-to-use rules, prerequisites, or alternatives. There's no comparison to sibling tools like 'expense-report' or 'receipt-generator' that might handle expense-related tasks differently.

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 carries the full burden of behavioral disclosure. It states the tool strips metadata, implying a mutation operation, but fails to describe critical traits such as whether the process is reversible, what permissions or inputs are required, how it handles errors, or the output format. The 'browser-based' hint adds minimal context, but overall, it's insufficient for a tool that modifies data.

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 and front-loaded, using only one sentence that efficiently conveys the core action and context. Every word earns its place, with no wasted text, making it easy for an agent to parse quickly.

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 (a mutation operation with no annotations and no output schema), the description is incomplete. It lacks details on behavioral aspects like safety, output format, or error handling. While concise, it doesn't provide enough context for an agent to reliably invoke the tool, especially compared to more descriptive siblings in the list.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately avoids discussing parameters, focusing instead on the tool's function. This meets the baseline of 4 for tools with no parameters, as it doesn't add unnecessary details 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 tool's purpose with specific verbs ('Strip') and resources ('GPS location, camera info, and metadata from photos'), making it easy to understand what it does. It distinguishes itself from siblings like 'pdf-metadata-remover' by specifying it's for photos and browser-based, though it doesn't explicitly contrast with all siblings. It avoids tautology by not just restating the name/title.

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 no guidance on when to use this tool versus alternatives. It mentions it's 'browser-based', which gives some context, but lacks explicit instructions on prerequisites, when-not-to-use scenarios, or comparisons to similar tools like 'pdf-metadata-remover' or 'image-crop'. This leaves the agent without clear usage direction.

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 mentions 'PDF output' and 'browser-based,' but lacks critical behavioral details: whether it's read-only or mutative, if it requires authentication, any rate limits, or what happens during execution (e.g., data processing steps). For a tool with zero annotation coverage, this is insufficient.

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 highly concise and front-loaded: the first part states the core functionality, and the second adds a useful constraint ('browser-based'). Both sentences earn their place by providing essential information without waste, making it easy to scan and understand.

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 (likely moderate, involving report generation), no annotations, no output schema, and 0 parameters, the description is minimally adequate. It covers the purpose and output format but misses behavioral transparency and usage guidelines. For a tool with no structured data to rely on, it should do more to explain how it works and when to use 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by implying the tool might use categories for expense reports, though it doesn't specify how these are provided (e.g., via UI or defaults). Since there are no parameters, a baseline of 4 is appropriate, as the description provides some context without redundancy.

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: generating 'category-based expense reports with PDF output.' It specifies the resource (expense reports) and output format (PDF), and distinguishes it from siblings like 'invoice-generator' or 'receipt-generator' by focusing on expense categorization. However, it doesn't explicitly mention the verb (e.g., 'generate' or 'create'), which slightly reduces specificity.

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 minimal guidance: it notes the tool is 'browser-based,' implying it might require a browser environment, but offers no explicit when-to-use rules, alternatives, or exclusions. For example, it doesn't clarify if this is for personal vs. business expenses or how it differs from similar tools like 'profit-loss' or 'cash-flow-statement.'

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 critical behavioral trait '(Browser-based tool)' indicating interactive UI flow rather than API return, and reveals 3-step workflow. However, missing output handling details (download vs URL vs inline) and persistence since no annotations cover safety/destructive hints.

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?

Extremely efficient: workflow arrows convey process sequence, parenthetical clarifies runtime environment. Every element earns its place with zero redundancy across 15 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?

Appropriate for a zero-parameter interactive tool. Covers initiation behavior and domain, though brief mention of output format (PNG/JPG) or return behavior would strengthen completeness given lack of output 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?

Zero parameters present, meeting baseline score of 4. Description implies configuration happens via browser UI (template selection, text input), compensating for empty schema by explaining how the tool accepts input despite formal parameter count of zero.

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?

Specific verb '生成' (generate), clear resource 'ブログ用画像' (blog eye-catch images), and distinct workflow 'テンプレート選択→テキスト入力→即生成' distinguishes it from generic image tools like image-resizer or collage-maker in the sibling list.

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?

Implies usage scope (blog images) and workflow, but lacks explicit when-to-use guidance versus siblings like stamp-maker or image-collage, and no mention of prerequisites or 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 are provided, so the description carries the full burden of behavioral disclosure. It mentions the conversion action but doesn't describe side effects (e.g., whether the original image is preserved), performance traits (e.g., speed or size limits), or error conditions (e.g., unsupported formats). For a tool with no annotations, this leaves significant gaps in understanding its 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, efficient sentence with zero waste. It front-loads the core purpose ('Convert between 11 image formats') and provides relevant examples without unnecessary elaboration. Every word earns its place, making it highly concise and well-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?

Given the tool's complexity (format conversion with quality settings) and lack of annotations or output schema, the description is insufficient. It doesn't explain what the tool returns (e.g., base64 output, error messages), how to handle unsupported formats, or the impact of quality settings. For a tool with no structured behavioral data, more descriptive context is needed.

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

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

Schema description coverage is 100%, so the schema fully documents the three parameters (image, quality, outputFormat). The description adds no parameter-specific information beyond implying format conversion, which is already covered by the schema's enum for outputFormat. This meets the baseline for high schema coverage, but doesn't enhance understanding of 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 tool's purpose: converting between image formats, listing specific examples (HEIC, WebP, PNG, JPG, AVIF). It uses a specific verb ('Convert') and identifies the resource ('image formats'). However, it doesn't explicitly differentiate from sibling tools like 'image-resizer' or 'image-to-pdf', which have related but distinct purposes.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an image input), exclusions (e.g., not for non-image files), or comparisons to siblings like 'image-to-pdf' or 'base64-converter'. Usage is implied by the tool's name and description but not explicitly 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?

No annotations provided. Description adds 'Browser-based tool' indicating interactive web interface rather than API calculation, but omits safety profile (read-only), whether it stores data, or whatoutput format users receive.

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 efficient sentence front-loaded with tax scope followed by implementation hint. No redundant text.

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?

Lists six complex tax types but lacks output schema description. Given complexity of Japanese freelance tax stack, could clarify that 'browser-based' implies user interaction required to view results, not automatic return.

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?

Zero parameters per input schema. Baseline 4 applies as no parameter documentation burden exists.

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?

Lists specific tax categories (所得税・住民税・事業税・国保・年金・消費税) distinguishing freelance-specific obligations (business tax, consumption tax) from employee-focused siblings like take-home-pay-calc. Title clarifies 'freelance' scope.

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 select this versus siblings like tax-return-calc (filing), salary-vs-freelance (comparison), or nhi-calc/social-insurance-calc (single-tax calculators). No prerequisites or constraints 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 are provided, so the description carries full burden. It mentions 'Auto-add' and 'Browser-based tool', hinting at automation and platform, but fails to disclose critical behaviors like input/output format, permissions, rate limits, or error handling. This leaves significant gaps for a tool with potential processing implications.

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 with two brief phrases: 'Auto-add reading aids to kanji by grade level. (Browser-based tool).' Every word contributes meaning, and it's front-loaded with the core purpose. No wasted sentences.

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 0 parameters and no output schema, the description is minimally adequate but incomplete. It lacks details on how the tool operates (e.g., input method, output format), behavioral traits, and usage context, which are crucial for a tool that modifies text. The absence of annotations exacerbates this gap.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds context about 'grade level' and 'Browser-based tool', which provides useful semantic information beyond the empty schema, though it's not strictly about 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 tool's purpose: 'Auto-add reading aids to kanji by grade level.' It specifies the action (add), resource (reading aids/kanji), and scope (by grade level). However, it doesn't explicitly differentiate from siblings, which are unrelated tools (e.g., calculators, generators, converters) with no direct alternatives for furigana addition.

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 minimal guidance with '(Browser-based tool)', implying it's for web use, but lacks explicit when-to-use instructions, prerequisites, or alternatives. No context on when to choose this over manual methods or other tools is 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?

No annotations are provided, so the description carries the full burden. It successfully discloses the browser-based nature and the specific calculation methodology (2000 yen self-burden). However, it lacks critical behavioral details: it does not specify the output format (HTML, JSON, text), whether the tool is idempotent, if it stores user data, or what interactive elements the browser interface contains.

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—one sentence with a parenthetical qualifier. The core functionality (reverse calculation of deduction limit) is front-loaded, followed by the specific constraint (2000 yen burden) and the implementation hint. There is no redundancy or extraneous text.

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 has zero parameters, no annotations, and no output schema, the description is minimally adequate but incomplete. It identifies what is calculated but not what the user receives (a URL, HTML content, or raw numbers). For a 'calculator' with no input parameters, it should explicitly state that it launches an interactive web interface or returns a form, rather than assuming the 'Browser-based' parenthetical suffices.

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 contains zero parameters, establishing a baseline score of 4. The description implicitly explains why parameters might not be needed (it describes a calculation target rather than inputs), referencing the 'browser-based' nature which suggests an interactive UI handles inputs. No additional parameter documentation is required or provided.

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 specific action (逆算/reverse calculation) and resource (控除上限額/deduction upper limit) for the Furusato Nozei (hometown tax) system. It specifies the unique constraint of '自己負担2,000円' (2,000 yen self-burden), which defines the calculation scope. However, it does not explicitly distinguish this from sibling tax calculators like 'tax-return-calc' or 'resident-tax-calc', though the domain specificity is implied.

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 minimal usage guidance. While the 'Browser-based tool' parenthetical hints at the interaction model, there is no explicit guidance on when to select this tool versus the numerous sibling tax calculators (e.g., 'freelance-tax-calc', 'withholding-tax-calc'). It does not state prerequisites (e.g., required income data) or when not 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 carries the full burden of behavioral disclosure. It states the conversion function but doesn't explain how the conversion works (e.g., formula, thresholds), what the output looks like, or any error handling. For a tool with 8 parameters and no annotations, this is insufficient.

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, efficient sentence with zero waste. It's front-loaded and directly states the tool's function without unnecessary details, making it easy to parse quickly.

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 complexity (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the conversion logic, output format, or behavioral traits like error handling. For a calculation tool with multiple inputs and no structured output, more context is needed for effective use.

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

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

Schema description coverage is 100%, so the schema fully documents all parameters with descriptions and defaults. The description adds no additional parameter semantics beyond implying three input scores (knowledge, thinking, attitude) are used, which is already covered in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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: converting three evaluation aspects into two grade systems (ABC and 5-level). It specifies the input (3-aspect evaluations) and output (ABC and 5-level grades), making the verb+resource explicit. However, it doesn't distinguish from siblings, as no similar grading tools are listed among siblings.

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 alternatives. The description lacks context about prerequisites, typical scenarios, or exclusions. It doesn't mention any sibling tools for comparison, leaving usage entirely implicit.

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 of behavioral disclosure. It states the tool computes hash values but doesn't mention any behavioral traits such as performance characteristics, error handling, or output format (e.g., hex string, base64). For a tool with no annotations, this leaves significant gaps in understanding how it behaves.

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—a single sentence—with no wasted words. It front-loads the core purpose ('Compute MD5, SHA-256, and other hash values'), making it easy to scan and understand quickly.

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 low complexity (two parameters, no nested objects) and high schema coverage, the description is minimally adequate. However, with no output schema and no annotations, it lacks details on return values (e.g., hash format) and behavioral context, which could be important for an agent invoking this 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 description coverage is 100%, with clear descriptions for both parameters ('text' and 'algorithm'). The description adds minimal value beyond the schema, only implying that multiple algorithms are supported. Since the schema already documents parameters thoroughly, the 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: 'Compute MD5, SHA-256, and other hash values.' It specifies the verb ('Compute') and resource ('hash values'), and lists example algorithms. However, it doesn't explicitly differentiate from sibling tools like 'uuid-generator' or 'base64-converter', which are also data transformation utilities but for different purposes.

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 no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context for hashing (e.g., security, data integrity), or comparisons with sibling tools like 'base64-converter' (encoding) or 'uuid-generator' (unique identifiers), leaving the agent to infer usage from the name alone.

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 carries full burden. Discloses critical 'Browser-based tool' trait indicating interactive/URL-opening execution, but omits what the tool returns (list of hashtags? opens browser window?) and any 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 highly efficient sentences with action front-loaded. 'Browser-based tool' parenthetical earns its place by disclosing execution environment. Zero waste.

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?

Adequate for a simple 0-param tool, but lacks description of return values or output behavior (critical given no output schema exists). 'Browser-based' hints at interaction model but could clarify what the agent receives back.

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 has 0 parameters, setting baseline at 4. Description mentions 'キーワードから' (from keywords), adding semantic context that the browser-based tool expects keyword input from the user, even though the agent passes no 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?

Specific verb (自動生成/auto-generate), clear resource (SNS用ハッシュタグ/SNS hashtags), and precise scope (TikTok/Instagram/X). Effectively distinguishes from sibling youtube-tag-generator (platform-specific) and sns-post-template (post templates vs hashtags).

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?

Lists supported platforms (TikTok/Instagram/X) providing implicit context for when to use (SNS marketing), but lacks explicit guidance on when to choose this over siblings like youtube-tag-generator or meta-description-generator.

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 of behavioral disclosure. It mentions 'removing dangerous tags and attributes,' which implies a read-only or transformation operation, but fails to detail critical aspects like error handling, performance implications, security guarantees, or what constitutes 'dangerous.' For a security-related tool with zero annotation coverage, this is a significant gap in transparency.

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, efficient sentence with zero waste—it directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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 moderate complexity (HTML sanitization with three parameters), no annotations, and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details on behavior, output format, or error handling. It meets the minimum viable threshold but has clear gaps in providing a complete context for safe and effective use.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters (html, level, removeEmpty) with descriptions. The description adds no additional meaning beyond what the schema provides, such as examples of sanitization levels or the impact of 'removeEmpty.' Baseline score of 3 is appropriate when the schema does the heavy lifting.

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 ('sanitize') and resource ('HTML'), specifying the action of removing dangerous tags and attributes. It distinguishes itself from other tools in the sibling list, which are unrelated to HTML processing. However, it doesn't explicitly differentiate from potential similar tools like 'html-formatter' or 'html-validator' that might exist elsewhere, keeping it from a perfect score.

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 no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It lacks context such as typical use cases (e.g., user input sanitization, content rendering) or comparisons with other tools in the sibling list, which are unrelated. This leaves the agent without explicit usage direction.

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 carries full burden. It effectively discloses output composition (four specific data points returned) but omits safety profile, error handling (timeouts, DNS failures), and side-effect risks.

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 12-word sentence with zero waste. Front-loaded with action ('Probe') and immediately followed by return value specification. 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?

No output schema exists, but description compensates by enumerating the four specific return components. Adequate for a simple 4-parameter probe tool, though error case documentation would improve it.

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

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

Schema has 100% description coverage (url, method, timeout, followRedirects all documented), establishing baseline 3. Description mentions 'redirect info' which semantically reinforces the followRedirects parameter's purpose, but adds no explicit parameter guidance.

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?

Specific verb 'Probe' + resource 'URL' + detailed outputs (status code, headers, response time, redirect info) clearly distinguishes this diagnostic tool from siblings (calculators, generators, converters).

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 when-to-use guidance or comparison to alternatives (e.g., og-preview which also likely fetches URLs). Description only states what it does, not when to choose 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 carries the full burden. It discloses key behavioral traits: the tool creates photos (implying a write operation) and operates locally without server uploads (privacy/security context). However, it lacks details on output format, quality, supported image types, or any limitations (e.g., browser compatibility, processing time).

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 short phrases) and front-loaded with the core purpose. Every word earns its place: 'Create passport/ID photos' states the action, and 'without uploading to any server. (Browser-based tool)' adds critical constraints efficiently. There is no wasted text.

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 (a photo creation tool with no parameters), the description is adequate but has gaps. It lacks an output schema, and without annotations, it doesn't fully cover behavioral aspects like output format or error handling. However, for a zero-parameter tool, it provides enough context to understand the basic purpose and privacy feature.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by clarifying the tool's scope (passport/ID photos) and operational context (browser-based, no server uploads), which goes beyond the empty schema. A baseline of 4 is appropriate as it compensates for the lack of parameters with meaningful context.

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: 'Create passport/ID photos' specifies the verb (create) and resource (photos), and 'without uploading to any server' adds a key constraint. However, it doesn't explicitly differentiate from sibling tools like 'product-photo-studio' or 'thumbnail-ctr-predictor', which might also involve image creation or manipulation.

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 through 'without uploading to any server' and 'Browser-based tool', suggesting privacy and local processing benefits. However, it doesn't provide explicit guidance on when to use this tool versus alternatives (e.g., 'image-crop' or 'bg-remover' for other photo edits), nor does it mention any prerequisites or 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'AI auto-correction' and 'Browser-based tool,' hinting at automated processing and execution environment, but lacks critical details: whether the tool modifies the original image, what output format to expect, any rate limits, or authentication needs. For a tool that likely alters images, this is insufficient.

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 short phrases that directly state the tool's function and technical context. Every word earns its place, with no redundancy or fluff. It's front-loaded with the core purpose, making it easy to scan.

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 (likely image processing with AI), lack of annotations, and no output schema, the description is incomplete. It misses key details: what the tool returns (e.g., a modified image file, a brightness score), how it handles errors, or any side effects. The agent lacks sufficient context to use this tool effectively beyond a vague understanding.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate. A baseline of 4 is applied since the schema fully covers the zero parameters, and the description doesn't introduce confusion.

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: 'AI auto-correction for dark or underexposed photos.' It specifies the action (auto-correction) and target resource (photos with brightness issues). However, it doesn't explicitly differentiate from sibling tools like 'image-color-picker' or 'image-crop' beyond the brightness focus, preventing a perfect score.

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 minimal usage guidance: it implies use for 'dark or underexposed photos' but offers no explicit when-to-use rules, prerequisites, or alternatives. The parenthetical '(Browser-based tool)' adds a technical constraint but doesn't help the agent choose between this and other image tools like 'bg-remover' or 'image-resizer'.

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 lacks critical behavioral details: it doesn't specify input methods (e.g., file uploads, URLs), supported image formats, output format (e.g., PNG, JPEG), size limits, or whether it's a read-only or mutating operation. The 'Browser-based' note is helpful but insufficient for a tool with potential complexity.

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 front-loaded: the first sentence clearly states the core functionality, and the second adds useful context ('Browser-based'). There's no wasted text, though it could be slightly more informative without losing efficiency.

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 0 parameters and no output schema, the description is minimally complete. It explains what the tool does but lacks details on behavior, inputs, and outputs. For a tool that likely involves image processing and user interaction, more context on limitations or usage 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, which is appropriate. Baseline is 4 for 0 params, as it avoids redundancy and focuses on the tool's 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 states the tool's purpose: 'Combine multiple photos into a single image with layout templates.' It specifies the verb ('Combine'), resource ('multiple photos'), and output ('single image'), and distinguishes it from siblings like 'image-crop' or 'image-resizer'. However, it doesn't explicitly differentiate from all image-related tools (e.g., 'image-to-pdf'), so it's not a perfect 5.

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

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

The description provides minimal usage guidance. It mentions the tool is 'Browser-based', which hints at execution context, but offers no explicit when-to-use rules, prerequisites, or alternatives. For instance, it doesn't clarify if it's for creating collages from uploaded files versus URLs, or when to choose this over other image manipulation tools.

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

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

With no annotations, the description carries full burden. It successfully discloses the browser-based nature and interactive eyedropper mechanism, but omits critical behavioral details like output format (HEX/RGB), persistence of extracted colors, or file size limitations.

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?

Extremely efficient two-part structure: first sentence states core function, second specifies mechanism and runtime environment. No redundant padding despite bilingual presentation.

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 tool with no output schema, the description covers the essential interaction model. However, given the server's extensive image-tool ecosystem (bg-remover, image-crop, etc.), it should clarify how images are fed into this browser tool (upload vs URL vs current view).

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?

Input schema has zero parameters, triggering the baseline score of 4. The description appropriately doesn't invent parameter documentation, though it implies image input is handled through the browser interface rather than schema 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?

Description clearly states the tool identifies/extracts colors from images using an eyedropper and automatic palette extraction. The phrase '画像から' (from image) and 'スポイト' (eyedropper) specifically distinguishes it from siblings like 'color-palette' (theoretical generation) and 'color-converter' (format conversion).

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?

While '(Browser-based tool)' hints at the interaction model, the description lacks explicit guidance on when to choose this over 'color-palette' or 'image-resizer', and doesn't explain prerequisites like image upload mechanisms despite having zero input parameters.

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 of behavioral disclosure. It mentions 'Browser-based tool', indicating it runs in a browser, but doesn't describe what the tool actually does behaviorally—such as whether it modifies images in-place, requires user interaction, or has any side effects. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 short phrases separated by a period. Every word earns its place: 'Drag-to-select cropping' defines the core action, 'with preset aspect ratios' adds a key feature, and '(Browser-based tool)' provides essential context. It's front-loaded with the main purpose and wastes no space.

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 has 0 parameters, no annotations, and no output schema, the description is minimally adequate. It states what the tool does and its environment, but lacks details on behavior, output, or integration with siblings. For a tool with such low complexity, it's complete enough to be functional but leaves gaps in understanding how it operates or what it returns.

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 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't add parameter details, but since there are no parameters, the baseline is 4. It implicitly suggests parameters might be handled via UI (drag-to-select), but doesn't explain semantics beyond that.

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 function: 'Drag-to-select cropping with preset aspect ratios.' It specifies the action (drag-to-select cropping) and key feature (preset aspect ratios), which distinguishes it from generic image tools. However, it doesn't explicitly differentiate from sibling tools like 'image-resizer' or 'smart-resize', which is why it's not a 5.

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

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

The description provides minimal usage guidance. It mentions 'Browser-based tool', which implies it requires a browser environment, but doesn't specify when to use this tool versus alternatives (e.g., 'image-resizer' for resizing without cropping, 'smart-resize' for automated adjustments). No explicit when/when-not or alternative recommendations are included.

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 of behavioral disclosure. It mentions 'aspect ratio lock' but fails to describe critical behaviors like whether the operation is destructive (e.g., overwrites original), performance characteristics (e.g., processing time), error handling, or output specifics. This leaves significant gaps 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?

The description is a single, efficient sentence with zero waste. It is front-loaded with the core purpose and avoids unnecessary elaboration, making it highly concise and well-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?

Given the tool's complexity (6 parameters, mutation operation) and lack of annotations and output schema, the description is insufficient. It omits behavioral details (e.g., side effects, error cases) and output information, failing to provide a complete context for safe and effective use.

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%, providing detailed parameter documentation. The description adds no additional parameter semantics beyond what's in the schema, such as explaining interactions between 'fit' and 'aspect ratio lock'. Baseline 3 is appropriate since the schema handles the heavy lifting.

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 with a specific verb ('Resize') and resource ('images'), and specifies 'exact pixel dimensions with aspect ratio lock' to clarify the operation. However, it does not explicitly differentiate from sibling tools like 'image-crop', 'smart-resize', or 'upscaler', which might have overlapping functionality, so it doesn't fully achieve sibling differentiation.

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 no guidance on when to use this tool versus alternatives. It lacks any mention of prerequisites, exclusions, or comparisons with sibling tools such as 'image-crop' or 'smart-resize', leaving the agent without context for 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool combines images into a PDF and is browser-based, but lacks details on permissions, rate limits, file size constraints, supported image formats, or output behavior. For a tool with zero annotation coverage, this is insufficient for safe and effective use.

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 and front-loaded: it states the core function in the first clause and adds a contextual note in parentheses. Every word earns its place, with no redundancy or unnecessary elaboration.

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 (simple conversion with no parameters) and lack of annotations or output schema, the description is minimally adequate. It explains what the tool does but lacks behavioral details (e.g., supported formats, limitations) and output information. It meets the bare minimum for a zero-parameter tool but leaves gaps in operational 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter details, which is appropriate. A baseline score of 4 is given because the schema fully covers the parameters (none), and the description does not need to compensate.

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: 'Combine multiple images into a single PDF document.' It specifies the verb ('Combine'), resource ('images'), and outcome ('single PDF document'), making the function unambiguous. However, it does not explicitly differentiate from sibling tools like 'pdf-join' or 'pdf-to-image', which prevents a perfect score.

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 minimal guidance: it mentions the tool is 'Browser-based,' which hints at usage context but does not specify when to use this tool versus alternatives (e.g., 'pdf-join' for merging PDFs or 'image-collage' for combining images without PDF conversion). No explicit when/when-not or alternative recommendations are included.

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 carries full disclosure burden. It adds 'browser-based tool' indicating execution context, but fails to clarify if this modifies site data (destructive vs read-only), required permissions, output format, or side effects like opening browser windows.

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?

Extremely concise two-sentence structure with zero waste: function sentence, benefit sentence, and technical parenthetical. Information is front-loaded with the core action (visualize) stated immediately.

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 zero input parameters and no output schema/annotations, the description adequately explains the tool's purpose but lacks crucial execution context. It should specify whether it returns visualization data, opens a browser UI, or modifies the site's link structure.

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?

Input schema has zero parameters, establishing baseline score of 4. The description correctly implies no user-supplied parameters are needed (works from internal article list), requiring no additional parameter documentation.

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

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

The description clearly states the tool visualizes internal link structures from article lists and optimizes flow to revenue articles (specific verb+resource). However, the meaning of 'browser-based tool' is slightly ambiguous (opens browser vs returns HTML), and it doesn't explicitly distinguish from potential SEO/analysis siblings.

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 versus alternatives (e.g., manual sitemap analysis), prerequisites (must have articles indexed?), or when-not-to-use. The implied usage relies solely on understanding the value proposition.

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 mentions 'simulation' which implies read-only/non-destructive behavior, but doesn't clarify if it's a calculation, projection, or what outputs to expect. It lacks details on rate limits, error conditions, or whether it requires authentication. The description is too brief to provide meaningful behavioral context beyond the basic purpose.

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—a single phrase with no wasted words. It's front-loaded with the core purpose. For a tool with comprehensive schema documentation, this brevity is appropriate and 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 tool's moderate complexity (7 parameters, no output schema, no annotations), the description is minimal but adequate as a starting point. The schema provides full parameter documentation, but the description doesn't address output format, error handling, or usage context. It meets minimum viability but leaves gaps in behavioral understanding.

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 parameters are well-documented in the schema itself. The description adds no additional parameter semantics beyond implying the tool handles NISA/iDeCo modes and compound growth. It doesn't explain parameter interactions, default behaviors, or provide examples. Baseline score of 3 is appropriate since the schema does the heavy lifting.

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 'NISA/iDeCo compound growth simulation' clearly states the tool's purpose as simulating compound growth for specific Japanese investment accounts (NISA/iDeCo). It uses specific terms ('compound growth simulation') and identifies the target resources, but doesn't explicitly differentiate from sibling tools, which appear to be various calculators and generators without direct overlap in investment simulation.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, typical use cases, or compare it to other investment calculators in the sibling list (e.g., 'npv-irr-calc', 'bond-yield-calc'). The user must infer usage from the tool name and parameters alone.

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 carries the full burden. It discloses that the tool is 'Browser-based' and outputs PDFs in '3 seconds', adding useful behavioral context about performance and execution. However, it doesn't cover aspects like error handling, authentication needs, or rate limits, leaving gaps 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?

The description is extremely concise with three short phrases, front-loading key information (compliance, output format, speed, and environment). Every sentence earns its place 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 no annotations, no output schema, and 0 parameters, the description provides basic purpose and behavior but lacks details on usage context, error cases, or output specifics. It's minimally adequate for a simple tool but has clear gaps in guiding effective use.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param details, which is appropriate, but it implies the tool generates invoices without specifying input requirements, slightly reducing clarity. Baseline is 4 for zero 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 states the tool generates invoices that are 'Japan qualified invoice compliant' with 'PDF output', which clarifies its purpose beyond the name/title. However, it doesn't specify what inputs are required or how it differs from sibling tools like 'receipt-generator' or 'purchase-order', making it somewhat vague.

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 alternatives. The description mentions 'Browser-based tool', which hints at the execution environment but doesn't specify use cases, prerequisites, or exclusions compared to other tools on the server.

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 mentions 'Create' (implying a write operation) and 'PDF export', but doesn't disclose behavioral traits like permissions needed, whether entries are saved or temporary, error handling, or rate limits. The 'Browser-based tool' note adds some context but is vague. For a mutation tool with zero annotation coverage, this is insufficient.

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: one sentence plus a parenthetical note. Every part earns its place by stating the core functionality and an important implementation detail (browser-based). It's front-loaded with the main purpose and wastes no 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?

Given the tool has 0 parameters, no annotations, and no output schema, the description is minimal but covers the basic purpose. However, for a 'create' operation, it lacks details on what happens after creation (e.g., where entries are stored, if PDF is downloadable), making it incomplete for full agent understanding. It's adequate but has clear gaps in behavioral 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?

The input schema has 0 parameters with 100% coverage, so no parameters are documented in the schema. The description doesn't mention any parameters, which is appropriate here. Since there are no parameters to explain, it meets the baseline expectation without needing to compensate for gaps.

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: 'Create debit/credit journal entries with PDF export.' It specifies the action (create), resource (journal entries), and additional capability (PDF export). However, it doesn't explicitly differentiate from sibling tools like 'balance-sheet' or 'profit-loss', which might be related financial tools, so it misses full sibling distinction.

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 no guidance on when to use this tool versus alternatives. It mentions it's 'Browser-based tool', which might imply usage context, but doesn't specify prerequisites, scenarios, or exclusions. Without explicit when/when-not instructions, it offers minimal usage direction.

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 of behavioral disclosure. It mentions 'tree view' as a feature, which adds some context beyond basic formatting, but fails to describe critical traits like error handling (e.g., validation failures), performance implications (e.g., large JSON handling), or output format details. This is inadequate for a tool with multiple functions.

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