JobDoneBot

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

With no annotations, the description provides some behavioral context (generates 10 patterns, includes CTR scores), but doesn't explain how the CTR score is calculated, whether it uses the current page content, or any limitations. This is a minimal disclosure for a tool with no structured params.

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

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

The description is a single sentence that is front-loaded with the core function and output. No wasted words, and the parenthetical 'Browser-based tool' adds minor context without bloat.

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 generation tool, the description covers the basics but leaves gaps: it doesn't specify language support, what 'CTR score' means in practice, or how the generated patterns are presented. Given no output schema, the description is the only source this info.

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

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

The tool has no parameters in the schema, so the description serves as the primary semantic source. It clearly indicates the input (article title) and output (10 patterns with CTR scores), which is sufficient for this simple tool.

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 10 patterns from an article title and includes CTR scores. The verb+resource is specific and understandable, but it doesn't explicitly distinguish itself from similar tools like thumbnail-ctr-predictor or title-multilingual.

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

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

There is no guidance on when to use this tool versus alternatives. The description implies it is for generating AB test title variations, but does not state contexts, exclusions, or 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?

With no annotations, the description carries the transparency burden. It discloses the calculation formula, reverse-calc capability, and browser-based nature, which is useful. However, it does not explain how the user inputs values, what the output looks like, or any 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?

The description is a single, information-dense sentence with all key elements front-loaded. Every phrase adds value—formula, purpose, reverse-calc, and platform—with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter, browser-based calculator, the description provides the essential formula and feature set. It is adequate for an agent to understand the tool's purpose, though it could mention the output format or how the calculation is displayed.

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, so the baseline is 4. The description adds context by naming the formula inputs (PV, CTR, CVR, unit price), which helps understand the tool even though they are not formal 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 a specific action: calculating monthly affiliate income using the formula PV×CTR×CVR×unit price, and mentions a reverse-calculation feature. The title, 'アフィリエイト報酬シミュレーター', distinguishes it from sibling revenue tools like youtube-revenue-calculator and views-simulator.

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 gives no guidance on when to use this tool versus alternatives. It does not mention scenarios that favor this simulator over sibling tools such as affiliate-revenue-dashboard or amazon-acos-calculator, nor does it state any 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 must convey behavior. It only states 'Browser-based tool' and vague references to tax filing, but doesn't clarify how data is input, what the user interaction is, or what the agent should expect when invoking the tool. This is a notable gap 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?

The description is concise, containing two short phrases in a single line. It front-loads the core function and adds a relevant use case. It could be slightly more structured but is efficient and free of 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?

Despite being a simple dashboard with no parameters, the description lacks crucial invocation details: what happens when the tool is called, whether it opens a browser UI, returns a report, or requires any state. The 'Browser-based tool' hint is minimal, and without an output schema, the agent cannot anticipate the tool's response.

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, the schema offers no semantics. The description compensates by explaining what the tool does overall, though it doesn't describe any specific inputs (since none exist). The baseline for 0 params is 4, and the description meets that by clarifying 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 function: managing affiliate compensation, PV, and CVR by client and month with graphical representations. It also mentions tax filing use, which distinguishes it from other dashboards by specifying its domain and 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?

It implies usage for monitoring affiliate revenue performance and tax preparation, providing clear context. It doesn't explicitly mention when not to use it or compare with alternatives like affiliate-revenue-calc, but the dashboard purpose is evident from the 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, and the description only notes 'Browser-based tool' without disclosing how input is supplied, what the output format is, or any limitations. This leaves the agent guessing about invocation 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 sentence that front-loads the output categories and adds a concise parenthetical note about being browser-based. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-parameter browser tool, the description covers the core purpose and outputs, but lacks explicit guidance on how a user's birth year is provided or when to invoke it relative to sibling tools, slightly limiting 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 tool has zero parameters, so the baseline is 4. The description adds context about the computations performed, which is sufficient given 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 uses a specific verb '一括表示' (display all at once) and lists concrete outputs (age, Japanese calendar, zodiac, constellation, school years), clearly distinguishing it from the sibling date-calculator 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 implies use for birth-year-to-age/calendar conversion, but provides no explicit when-to-use guidance or comparisons to alternatives like date-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?

No annotations are provided, so the description must fully disclose behavior. It only mentions 'Browser-based tool' and instant calculation, but does not explain how the tool is invoked, whether user input is required (the schema has no parameters), what the output/return behavior is, or any limitations. This leaves significant opacity for an agent.

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

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

The description is a single sentence that front-loads the core functionality (ad cost to ACoS/ROAS/break-even CPC) and appends the browser-tool nature. Every word earns its place; there is no filler 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?

For a 0-parameter browser-based calculator with no output schema, the description is thin. It communicates what is calculated but not the user workflow (e.g., how the agent should interact with the browser tool, what the user will see, or how results are delivered). Given no annotations and no output schema, the description should provide more 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, so schema coverage is 100% and the baseline is 4 per the rubric. The description adds no parameter details, but none are needed; it does not clutter with irrelevant 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 calculates ACoS/ROAS and break-even CPC from advertising cost, using the specific verb 算出 (calculate). The input-to-output mapping (広告費→...) is explicit, and the metrics named distinguish it from sibling calculators.

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 intended usage is implied by the metric names (ACoS, ROAS, CPC), but the description provides no explicit guidance on when to use this tool over alternatives like amazon-fba-calculator or rakuten-fee-calculator. No when-to-use or when-not-to-use conditions are stated.

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

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

With no annotations, the description must carry the full burden of behavioral disclosure. It mentions 'Browser-based tool' and automatic size classification, but does not explain how the tool accepts input (given zero schema parameters), whether it requires user interaction, or what output format to expect. This leaves important behavioral traits unclear.

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 short sentence covering function, components, and an algorithmic trait. It is front-loaded with the core purpose and contains no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter browser-based tool, the description is minimally viable: it states purpose and output. However, it lacks guidance on how an agent should invoke or interact with a browser-based tool, or any caveats (e.g., region-specific fees, required user inputs). The 'browser-based' note adds some context but is insufficient for full 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 schema has zero parameters, so the baseline is 4. The description conceptually names the main inputs (FBA fees, storage fees, shipping fees) and notes automatic size classification, which adds meaning beyond the empty schema. Since there are no formal parameters, this is adequate.

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

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

The description clearly states the tool's function: calculating profit from FBA fees, storage fees, and shipping fees, with automatic size classification. The verb '計算' (calculate) is specific to a resource, and it distinguishes itself from siblings like amazon-acos-calculator by focusing on total profit rather than a single metric.

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

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

There is no explicit guidance on when to use this tool versus alternatives. It does not mention any alternatives, exclusions, or prerequisites. The only implicit signal is that it is for profit calculation involving FBA costs, but that's not enough to guide selection among the many calculator siblings.

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

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

With no annotations, the description carries the transparency burden. It does provide useful behavioral context: the tool is browser-based and performs a defined calculation. However, it doesn't disclose what the output looks like, whether data persists, or any limitations, so transparency is only partially addressed.

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

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

The description is a single, compact sentence with a clear formula and a platform qualifier. It is front-loaded and contains no filler or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 0-parameter browser calculator with no output schema, this is minimally sufficient: it states the calculation logic and the core outputs. However, it leaves gaps around what the user actually receives (e.g., what 'optimal inventory' and 'order timing' mean numerically, or the interface format), so completeness is moderate.

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 and coverage is 100%, so there are no parameters to describe. The baseline for 0 parameters is 4, and the description adds the clarifying context that this is a browser-based tool rather than an argument-driven API.

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: calculate optimal inventory and ordering timing from purchase quantity and sales speed ('仕入れ数×販売速度→適正在庫・発注タイミングを計算'). It identifies the domain (Amazon inventory) and a specific calculation, but does not explicitly differentiate it from sibling Amazon calculators like amazon-fba-calculator or amazon-sales-dashboard.

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 is given on when to use this tool versus alternatives. The formula implies it is for inventory planning, but there is no mention of prerequisites, scenarios, or exclusions. The only added context is 'Browser-based tool', which is more about invocation than usage guidance.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It does not explain how the product name is provided (e.g., from the current page), whether the tool performs side effects, or what the exact behavior is. The 'Browser-based' tag is vague and insufficient for understanding the tool's 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 sentence with no redundancy, directly stating the action and resource. It is appropriately sized and front-loaded, with every word earning 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 absence of annotations, an empty schema, no output schema, and a large list of sibling tools, the description is too thin. It does not clarify what 'browser-based' entails operationally, nor does it explain the output format or conditions for use, making it incomplete for an agent to rely on.

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, so the description's '商品名から' (from product name) is the only indication of input. Since there are no formal parameters, the description adds the essential semantic meaning for the expected input, meeting the baseline for 0-param 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 function: '商品名からSEOキーワードを分解・サジェスト生成' (decompose/suggest SEO keywords from product name), which identifies the verb and resource. It also adds 'Browser-based tool' to hint at the environment, but it does not explicitly differentiate from other keyword-related tools like keyword-difficulty-checker.

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 gives no guidance on when to use this tool versus alternatives. It lacks details on prerequisites, typical use cases, or exclusions. The only hint is 'Browser-based tool,' which does not convey the practical context for an agent to decide when to invoke 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?

With no annotations, the description carries the full burden and does disclose that data is stored in localStorage and the tool is browser-based, indicating client-side persistence. However, it omits important behavioral details such as data lifecycle, input methods, storage limitations, or what happens if localStorage is cleared.

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, consisting of two short clauses that convey the core functionality and storage mechanism without unnecessary words. Information is front-loaded and highly scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that there is no input schema, output schema, or annotations, the description provides adequate high-level context: ASIN-level metrics, monthly trend graph, and localStorage persistence. It could mention how data is entered or exported, but this is not essential for basic invocation of a dashboard tool with no parameters.

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 accepts zero parameters, so the description appropriately focuses on the tool's functionality rather than parameter syntax. Baseline of 4 applies because there are no parameter semantics to explain.

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 manages ASIN-specific sales, profit, and inventory data using localStorage, and displays monthly trend graphs. This specific verb+resource combination distinguishes it from the many Amazon-related calculators 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?

The description implies client-side usage via 'localStorage' and 'Browser-based tool,' but does not explicitly state when to choose this over alternatives like affiliate-revenue-dashboard or other Amazon calculators. No exclusions or alternative recommendations are provided.

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 only says 'Browser-based tool,' which gives a tiny bit of context (runs in browser), but it doesn't state whether the tool is read-only, whether it stores data, or whether it requires user input. For a tracking/management tool, this lack of behavioral clarity is a notable 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 two short fragments: 'Accounts receivable/payable tracking with aging analysis. (Browser-based tool)' It is extremely concise, front-loaded with the core purpose, and contains no fluff. Every word earns its place, and the parenthetical adds a useful execution context. This is a model of brevity.

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, simple tool without an output schema, this description is reasonably complete. It tells the user what the tool does (AR/AP tracking with aging) and that it's browser-based. It doesn't explain the output format or whether it generates reports, but given the low complexity, the description covers the essentials. Slightly higher would require mentioning features, but it's adequate.

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 is empty (0 parameters), so the description is not required to explain any parameters. Per the rubric, 0 params earns a baseline of 4. The description doesn't need to compensate for schema gaps because there are none. It could have mentioned if data is entered via file upload or imports, but that's beyond parameter semantics.

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

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

The description clearly identifies the tool's domain: 'Accounts receivable/payable tracking with aging analysis.' This is specific enough to distinguish it from siblings like balance-sheet or cash-flow-statement, though it lacks an explicit imperative verb. It's clear what the tool is for, but it could be sharper with a phrasing like 'Tracks AR/AP and provides aging analysis.'

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

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

There is no guidance on when to use this tool versus alternatives. It does not mention any specific use cases, prerequisites, or situations where another tool would be more appropriate. This is a common gap for simple tools, but it's still a missing piece.

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 burden of behavioral disclosure. It mentions 'Browser-based tool' and 'テンプレート付き', but does not elaborate on output format, limitations, or data handling. This is a non-mutating generator, so minimal disclosure is acceptable, but some behavioral aspects remain unstated.

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 that communicates the core transformation (keyword → heading structure), a key feature (templates), and an operational note (browser-based). Every word earns its place, and it is front-loaded with the primary action.

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, empty schema, and lack of output schema, the description is largely sufficient. It covers the purpose, a key feature, and operational context. It does not specify details like heading count or template variety, but these are not essential for basic 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 input schema is empty (0 parameters), so the baseline is 4. The description adds semantic context by mentioning 'KW入力' (keyword input), which clarifies the intended user input even though no formal parameter exists. This aligns with the tool's interactive browser-based 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 tool's function: it takes a keyword input and automatically suggests H2/H3 heading structures. The verb '提案' (suggest) and resource 'H2/H3見出し構成' (H2/H3 heading structure) are specific, and it distinguishes itself from siblings like chapter-list-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?

The description implies usage for article outlining via keyword input but does not explicitly state when to use it vs. alternatives or provide exclusions. The context is clear enough that an agent could infer when to invoke it, but there is no explicit guidance.

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

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

With no annotations, the description carries the full burden. It mentions the browser-based nature, but does not disclose how inputs are supplied (especially given the empty schema), what the output format is, or whether there are any side effects. This is a significant gap for an agent deciding how to invoke the 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 concise with a front-loaded action and resource. The parenthetical is extra but acceptable. However, 'B/S' is an abbreviation that might cause ambiguity, slightly reducing clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema and no annotations, the description is too thin. It doesn't explain what the tool returns (e.g., a printable statement, a visual report) or how the agent should provide the three components, making the tool incomplete for reliable 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 schema has zero parameters, so the baseline is 4. The description adds meaning by naming the conceptual inputs (assets, liabilities, equity) and indicates they are required for creation, compensating for the lack of structured 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 creates a balance sheet ('Create B/S') from three accounting components: assets, liabilities, and equity. This distinguishes it from siblings like cash-flow-statement or profit-loss, though the abbreviation 'B/S' could be clearer.

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

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

There is an implied usage context: use it when you have the three components of a balance sheet. The parenthetical 'Browser-based tool' hints at a UI-led workflow, but the description does not explicitly state when to use this over alternatives or provide 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 the full burden. It only adds 'Browser-based tool', which hints at where it runs but does not disclose output format, resolution, download behavior, or limitations. This is minimal behavioral information for a tool with no other metadata.

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

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

The description is a single sentence that front-loads the core function and supported formats. It is extremely concise with no filler or redundant information, earning every word.

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, parameter-less tool, the description gives the essential functionality. However, it lacks details about the output (e.g., image size, format), browser-specific behavior, or limitations. Given the absence of output schema and annotations, a bit more detail would improve completeness, but it is minimally adequate.

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 is empty (0 parameters), and schema description coverage is 100%. The description adds no parameter details because there are none to document, which is appropriate. The baseline for 0 parameters is 4, and the description does not need to compensate for missing schema fields.

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

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

The description specifically names the tool's function: 'Generate JAN, EAN, Code128 barcodes'. This clearly identifies the verb (generate), the resource (barcodes), and specifies supported formats, distinguishing it from sibling tools which are unrelated.

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 context is implied: use when you need barcode generation. However, no explicit guidance is given on when to use this over alternatives or any prerequisites/exclusions. Given the tool name and description, the usage is self-evident 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?

With no annotations, the description carries the full burden of behavioral disclosure, but it only states the core operation. It also claims support for 'files' despite the input schema containing only a text parameter, which is misleading. No mention of output format, mode defaults, or URL-safe 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, concise sentence that is immediately understandable and front-loaded. However, its brevity sacrifices important behavioral details, so while it earns its place, it is not fully sufficient.

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 three parameters and no output schema, the description is too sparse. It does not explain the output format, that mode defaults to encode, or how urlSafe changes behavior. The 'files' claim is contradicted by the schema, leaving the description incomplete and somewhat misleading.

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 already provides descriptions for all three parameters (mode, text, urlSafe) with 100% coverage, so the description adds no additional parameter semantics. The mention of 'files' could actually confuse parameter expectations, but the schema itself is clear.

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 a specific action (encode/decode) and resource (text/files to Base64), making its purpose unambiguous and distinguishing it from sibling tools like hash-generator or url-encoder.

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 URL-encoder or string-transform. The use case is only implied by the tool's name and description, offering no explicit context 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 the full burden. It adds useful context by disclosing the fee components (3% service fee + payment fee) and the comparison aspect, and notes it's a browser-based tool. However, it does not describe the interaction details (e.g., form inputs, output format, or lack of persistence), which would improve 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, compact sentence that is front-loaded with the primary purpose, followed by the plan comparison and a parenthetical note about being browser-based. Every word contributes value, with no redundancy or 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 tool's low complexity (0 params, no output schema, no annotations), the description adequately covers the core purpose, fee details, and plan comparison. It could be slightly more complete by mentioning the exact payment fee rate or user interaction flow, but these are minor gaps.

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

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

With zero parameters, the schema coverage is trivially 100%, and the baseline for 0 params is 4. The description adds meaning by explaining what the calculator does, indirectly indicating what user inputs might be needed (e.g., sales amount, plan type), even though it doesn't enumerate them.

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

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

The description clearly states it calculates profit after service fees (3%) and payment fees, and compares Standard/Growth plans. This is a specific verb+resource (BASE fee calculator) that distinguishes it from other fee calculators like rakuten-fee-calculator or mercari-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 description implies the tool is for BASE fee and profit calculations, and the plan comparison suggests when it's relevant, but it doesn't explicitly state when to use this tool vs alternatives or provide exclusions. No sibling mentions or alternative references are given.

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

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only mentions 'browser-based' and 'AI', but does not disclose limitations, output format, or how the image is provided. This is a significant gap for a tool that presumably processes user-supplied images.

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, fitting all essential information into a single sentence with a useful parenthetical. No wasted words or redundant details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description fails to mention what the result is (e.g., a processed image) or how the input is provided. This leaves agents uncertain about invocation and return values, making the description incomplete for practical 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 zero parameters, so the schema is inherently complete. The description does not need to add parameter details; the 0-parameter baseline of 4 applies, especially since no parameter information is omitted or misleading.

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 a specific verb ('removal') and resource ('background') for people, products, and objects, clearly stating the tool's function. However, it does not distinguish from sibling tools like 'bg-remover-pro' or 'pro-matting', so it earns 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?

No guidance is provided on when to use this tool versus alternatives such as 'bg-remover-pro'. The description only implies one-click simplicity, but it lacks explicit context or exclusions, resulting in no practical usage guidance.

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

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

With no annotations, the description carries the behavioral disclosure burden. It discloses precision handling of difficult subjects, transparent PNG output, and browser-based execution, which implies local processing. It does not mention limitations or privacy, but these are less critical for a parameterless browser 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, front-loaded sentence that efficiently conveys the core value proposition, quality differentiator, and output format 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 zero-parameter browser tool, the description adequately covers what it does, the output format, and how it executes. It lacks input format or size limitations, but these are not essential for selecting or invoking a parameterless 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 has zero parameters, so there are no parameter semantics to clarify. The baseline of 4 applies because the description does not need to compensate for missing 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's function: precise cutout of hair and transparent objects, positioning it as the high-quality version. It also specifies the output format (transparent PNG), distinguishing it from the standard bg-remover sibling.

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 '高品質版' implies using this tool when high-quality cutouts are needed, but it does not explicitly state when to prefer it over alternatives like bg-remover or pro-matting. No exclusions or direct comparisons are provided.

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 behavioral burden. It only names the outputs, but does not disclose how the tool behaves (e.g., calcMode behavior, input requirements, assumptions, output format). The agent cannot anticipate edge cases or operational constraints.

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, front-loaded sentence with zero wasted words. It efficiently states the core functionality without redundancy or 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?

Despite having 7 parameters and no output schema or annotations, the description does not explain calculation modes, how inputs relate to outputs, or return value structure. Critical contextual information for correct tool invocation is missing.

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

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

Schema coverage is 100% for all 7 parameters, so the schema already documents inputs. The description adds no parameter-specific meaning beyond naming the three financial metrics, which map to the tool's purpose rather than parameter semantics. Baseline 3 applies.

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

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

The description specifies the tool's outputs (yield to maturity, duration, convexity), clearly distinguishing it from sibling calculators like npv-irr-calc or investment-simulator. The verb is implied through 'calculator,' but it lacks an explicit action like 'calculates.'

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 simply states what it is, leaving the agent to infer contexts like bond valuation. There are no exclusions, prerequisites, or alternative tool references.

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 must carry the full burden of disclosing behavior. It only mentions 'Browser-based tool' and '3 format styles', but does not explain how the user interacts with it, what inputs are required, what output is produced (e.g., PDF, HTML), or any side effects. This is a significant gap for a tool with zero annotation coverage.

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, consisting of a single sentence plus a parenthetical. Both pieces of information ('Professional CV in 3 format styles' and 'Browser-based tool') are relevant and non-redundant. It is front-loaded and 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?

Despite having no parameters and no output schema, the description leaves major gaps: it does not explain what 'career history' refers to, how the tool is invoked (despite claiming browser-based), what the output looks like, or how it differs from the similar 'resume-generator' sibling. This makes the tool under-specified for an agent to use reliably.

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, so the schema is trivially 100% covered. The description adds context by mentioning '3 format styles', which is an output characteristic rather than a parameter. Since there are no parameter semantics to explain, the baseline of 4 is appropriate.

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

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

The description 'Professional CV in 3 format styles' clearly identifies the tool as producing CVs and specifies a concrete scope (three styles). It is not a tautology, but it does not explicitly differentiate from the sibling tool 'resume-generator', which likely has overlapping 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?

The description provides no guidance on when to use this tool versus alternative tools like 'resume-generator' or any other CV-related tool. It lacks both inclusion criteria and exclusions, leaving the agent without context for 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 must fully disclose behavioral traits. It does not explain what inputs are needed (besides interacting in a browser), how to provide financial data, what the output format is, or any limitations of the indirect method. The parenthetical about being browser-based is minimal context, leaving significant behavioral uncertainty.

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 stating the core purpose followed by a short parenthetical. It is front-loaded with the main function and contains no unnecessary words. This is appropriately sized for the simple structure.

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?

Despite the simplicity, this tool is likely a complex financial statement generator without an output schema or parameter definitions. The description does not explain how to use it, what data it consumes, or what it produces. With sibling tools like balance-sheet and profit-loss, more contextual guidance is necessary to differentiate and to set expectations. The description is insufficient for an agent to know how to invoke or interpret this 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 tool has zero parameters and the schema reflects that with an empty object, so the schema description coverage is 100%. The description adds no parameter information, but none is needed. Baseline for 0-parameter tools is 4, and there is nothing missing here.

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: 'Indirect method cash flow statement generation.' This includes a specific verb ('generation'), a resource ('cash flow statement'), and a distinguishing detail ('Indirect method'), which separates it from sibling tools like balance-sheet and profit-loss that also generate financial statements.

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 such as balance-sheet or profit-loss. It does not mention use cases, prerequisites, or exclusions. The only additional hint is '(Browser-based tool)', which is trivial and not about selection criteria.

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 browser-based and the features, but does not disclose what happens when invoked (e.g., output format, whether it opens a UI, whether files are downloaded) or any requirements/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?

One concise sentence plus a brief parenthetical. No wasted words, and the purpose is stated first. It is well-structured and easily scannable.

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 no parameters, no output schema, and no annotations, the description is relatively minimal. It tells what the tool does but omits operational details like expected inputs, output behavior, or how the browser-based nature affects usage. It is adequate but not rich.

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?

There are zero parameters (empty schema), so the baseline is 4. The description adds context by mentioning templates and mail-merge, which hints at what configuration might be involved, even though no formal parameters are exposed.

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 ('Award') and resource ('certificates'), and highlights key features (templates and name mail-merge). This distinguishes it from all sibling tools, none of which mention certificates.

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

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

The description implies usage for creating certificates, and the parenthetical 'Browser-based tool' gives a context clue. However, it does not explicitly state when to use this tool versus alternatives or provide any 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 the full burden of behavioral disclosure. It only mentions 'Browser-based tool', which provides a minimal hint about how the tool operates, but it does not disclose whether the tool is client-side, read-only, or what happens to the input data. This is a significant gap for a tool with no annotations.

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

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

The description is a single, efficient sentence that front-loads the core action and output format. Every word earns its place, with no wasted content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (no parameters, no output schema), the description is largely sufficient. The 'Browser-based tool' qualifier is useful context for invoking it. However, it could have mentioned the expected input format (e.g., timestamps or duration markers) to fully eliminate ambiguity for an agent.

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

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

There are zero parameters in the schema, so the baseline is 4. The description adds semantic value by explaining the tool's input (video segment boundaries) and output (YouTube chapter format), which gives an agent a clear conceptual model of the tool's functionality even though no formal parameters 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?

The description clearly states the tool's function with a specific verb and resource: it takes video segment boundaries as input and outputs them in YouTube chapter format. This distinguishes it from siblings like timestamp-generator, which serve a related but different 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?

The description gives no explicit guidance on when to use this tool versus alternatives such as timestamp-generator or youtube-description-generator. The only hint is 'Browser-based tool', which indicates it is UI-driven but does not help an agent choose among YouTube-related 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 present, so the description carries the full burden. It mentions 'search and custom additions' as behaviors, but does not disclose whether custom additions persist, require permissions, or have side effects. Lacks detail on what the tool actually does beyond these 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?

The description is one short sentence plus a parenthetical, with no filler. It is efficient and front-loaded, though it omits some potentially useful content. Still, it is appropriately concise for a simple tool.

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?

Despite 0 parameters and no output schema, the description is incomplete for an agent to know what to expect. It does not describe the return format, how 'custom additions' are handled, or how the tool integrates into an accounting workflow. The 'Browser-based tool' tag is generic and not very informative.

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 is empty (0 parameters), so there is no parameter detail to explain. The description does not need to compensate for any undocumented parameters, earning the baseline score for 0-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 states the tool provides '100+ standard accounts with search and custom additions,' which conveys the resource and capabilities but lacks an explicit action verb. It vaguely distinguishes from siblings like balance-sheet or journal-entry by emphasizing a prebuilt list of accounts, but could be clearer.

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 trial-balance. The phrase 'Browser-based tool' hints at the environment but does not give selection criteria 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, the description carries full burden for behavioral disclosure. It implies a read-only check but does not explicitly state that it's safe, does not describe possible status values or side effects, and gives no information about return behavior, all of which are critical for an agent.

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, front-loaded sentence that directly states the purpose with no redundant phrasing. It is appropriately sized for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description should explain return values or status semantics, but it does not. The meaning of 'status' for a checkout session is left undefined, and there's no mention of errors or edge cases, making the tool incomplete for an agent to invoke confidently.

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 covers 100% of the single parameter (session_id) with a clear description ('Stripe checkout session ID (cs_xxx)'). The tool description adds no further parameter details, but the baseline of 3 applies due to 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 a specific action ('Check') and resource ('JobDoneBot checkout session'), which is unambiguous. It distinguishes from siblings by focusing on session status rather than subscription purchase, though it doesn't explicitly name 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 guidance on when to use this tool versus alternatives, no prerequisites, and no context such as typical scenarios. It only states what the tool does, leaving usage entirely to the agent's inference.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It does disclose that the timer is full-screen, browser-based, and makes chime sounds, which are useful behavioral traits. However, it omits details such as how the duration is set, whether audio permissions are needed, or how the user exits full-screen, leaving some 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 two short sentences and completely front-loaded with the essential information. Every word adds value, and the parenthetical 'Browser-based tool' is a useful clarification without adding bulk.

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?

As a simple no-parameter browser tool, the description captures the core function well. However, the existence of a closely named 'countdown-timer' sibling creates ambiguity, and the absence of usage context or behavioral details (e.g., configurable duration, audio behavior) leaves some completeness gaps. Given the tool's low complexity, the description is adequate but not fully robust.

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 and the schema is fully covered, so on the baseline of 4 applies. The description does not need to explain parameter meanings because there are none, and it adds no misleading parameter semantics.

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 as a full-screen countdown timer with chime sounds, which conveys its core function. It does not use an explicit verb, but 'timer' implies the action. It also implicitly distinguishes from the generic 'countdown-timer' sibling by noting the classroom context and chime feature, though it could be more explicit.

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 the similar 'countdown-timer' sibling or any alternatives. It does not state the intended use case (e.g., classroom timing) or any exclusions, leaving the agent to infer when it should be selected.

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. 'Format source code' implies a pure transformation, but it does not disclose return value, error behavior on invalid input, or configuration defaults beyond the schema. Adequate but with 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?

A single front-loaded sentence states the purpose, engine, and supported languages without redundancy. 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?

The tool is a straightforward formatter with a comprehensive schema covering all parameters. No output schema exists, and the description omits explicit return/error details, but the purpose and inputs are sufficiently clear 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 each of the 8 parameters is already documented. The description adds no additional parameter semantics beyond listing supported languages, which are also in the schema's language enum. Baseline 3 is appropriate.

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

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

The description uses a specific verb ('Format'), identifies the resource ('source code'), and names the engine ('Prettier') plus the supported languages. This clearly distinguishes it from sibling tools like sql-formatter, which is not in the supported language 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?

The supported language list provides clear context for when this tool applies. It does not explicitly mention alternatives or exclusions (e.g., SQL via sql-formatter), but the context is unambiguous for standard code formatting.

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 only states the conversion function and the presence of a color picker, without revealing how invalid inputs are handled, what output format is returned, or any potential side effects. This is minimal transparency for a tool that processes user-supplied strings.

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, consisting of a single sentence that front-loads the core function. No filler words or redundant information are present, making it efficient for quick agent scanning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple conversion tool, the description covers the primary purpose, and the schema fully documents parameters. However, without an output schema or behavioral notes, the description does not explain return formats or edge cases. Given the low complexity, this is adequate but leaves room for improvement.

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

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

Schema description coverage is 100%, with both parameters ('input' and 'fromFormat') having descriptive text and examples. The description adds no extra meaning beyond the schema, so the baseline of 3 is appropriate per the rubric.

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: mutual conversion between HEX, RGB, HSL, and CMYK color formats. This specific verb-resource pair distinguishes it from sibling tools like color-palette or image-color-picker, which focus on generation or extraction rather than 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?

No explicit usage guidance is provided. The description does not mention when to use this tool over alternatives, nor does it state any prerequisites or exclusions. The only hint is the mention of a color picker, which implies an interactive use case but is not clearly articulated.

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 responsibility for behavioral disclosure. It adds only the note 'Browser-based tool,' which hints at execution environment but does not explain how palettes are generated, what output is produced, or any limitations. This is minimal behavioral context.

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

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

The description is extremely concise, consisting of one main sentence plus a short parenthetical. The core purpose is front-loaded ('Generate harmonious color palettes'), and no redundant or filler content is present. Every word contributes to 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 absence of an output schema and annotations, the description is quite thin. It does not explain what a 'palette' looks like (e.g., number of colors, format), how the 'harmonious' generation works, or whether any user interaction is required. For a simple browser tool this may be acceptable, but the lack of return-value or interaction details leaves gaps.

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

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

The input schema has zero parameters, and the schema description coverage is 100%. Since there are no parameters to document, the description is not required to add parameter details. The baseline of 4 applies because the schema fully covers the (empty) parameter set.

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: 'Generate harmonious color palettes for design projects.' The verb 'Generate' plus the resource 'color palettes' precisely identifies the action and output. It distinguishes itself from related sibling tools like color-converter (conversion) and image-color-picker (extraction).

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 'for design projects' implies the context of use but does not explicitly state when to choose this tool over alternatives. No exclusions or alternative tool names are mentioned, leaving the agent to infer appropriate usage solely from the design-project qualifier.

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

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

With no annotations, the description carries the full burden. It discloses that the tool is browser-based and generates copy-pasteable HTML for WordPress, adding useful behavioral context beyond the simple action. It does not mention any limitations or side effects, but for a 0-parameter client-side tool, it is reasonably transparent.

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

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

The description is a single concise sentence plus a parenthetical, every word earns its place. It front-loads the core function and adds useful usage context without wasting 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's low complexity (no params, no output schema), the description is sufficient to understand its purpose and output. It mentions the output format (HTML), target platform (WordPress), and speed, which covers the essential context an agent needs.

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

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

The tool has no parameters, so the schema is trivially complete. The description correctly implies no inputs are required, which aligns with the empty schema. The baseline for 0 params is 4, and nothing in the description contradicts this.

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

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

The description clearly states it generates product comparison table HTML, which is a specific verb and resource. It implies a distinct purpose, though it does not explicitly contrast with sibling tools that also generate HTML or templates.

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 by mentioning it can be pasted into WordPress and generates output in 30 seconds. However, it does not provide explicit when-to-use vs alternatives or exclusions, leaving the user to infer the best scenario.

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, but it only mentions 'Generate' and 'Browser-based.' It does not explain what the user sees, whether a document is downloaded, or any interactive steps, leaving the actual behavior unclear.

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 short and front-loaded with the core action, but the parenthetical 'Browser-based tool' adds little value and is ambiguous. It is concise without unnecessary bulk, though it could be more informative.

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?

Even for a zero-parameter tool, the description is too thin. It doesn't specify the output format, how templates are chosen, or what happens when invoked, leaving significant gaps for an agent trying to select and use the tool correctly.

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

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

The tool has zero parameters, so the schema provides complete coverage. The description doesn't need to explain parameters, and the baseline of 4 applies because there is nothing to add.

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 business contracts from templates, using a specific verb and resource. It distinguishes itself from generic document tools, though it doesn't explicitly contrast with sibling legal generators like NDA or terms generators.

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

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

There is no guidance on when to use this tool versus alternatives such as nda-generator or terms-generator. The parenthetical 'Browser-based tool' is vague and doesn't clarify when it should be selected.

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 'リアルタイムカウントダウン' (real-time countdown) and 'Browser-based tool', but these are ambiguous: 'real-time' conflicts with the 'how many days' phrasing, and it doesn't specify whether the display updates by the second or just shows a static day count. It also omits details like whether it uses the system's current date or requires user input.

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, front-loaded sentence that immediately conveys the tool's purpose with a catchy question, followed by a brief parenthetical noting it's browser-based. No words are wasted, and all information is relevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description must explain what the user sees. It says 'how many days until Christmas/New Year/GW', which conveys the core output, but the 'real-time countdown' phrase adds ambiguity about the actual display (e.g., days only vs. hours/minutes/seconds). For a zero-parameter tool, the description is nearly complete but falls short due to this internal inconsistency.

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, so the baseline score is 4 per the rubric. The description doesn't need to explain parameters, and it doesn't attempt to, which is appropriate given there is nothing to configure.

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 counts down days until Christmas, New Year, and Golden Week, using a specific question format ('あと何日？') that identifies the resource and action. It distinguishes itself from general date calculators and classroom timers by focusing on these specific holiday countdowns, though it doesn't explicitly mention 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 usage is implied: use this tool to see how many days remain until the listed holidays. However, no explicit when-to-use or when-not-to-use guidance is provided, nor are any sibling alternatives like 'date-calculator' mentioned for general date calculations.

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 burden of behavioral transparency. It only states the tool's core function without disclosing output format, error handling, side effects, or any other behavioral details. This is minimal coverage for an agent that needs to know what to expect when invoking the 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, front-loaded sentence that uses concise language. Every word contributes to communicating the tool's purpose, with no redundancy or 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, the description should clarify what the tool returns (e.g., parsed description or generated expression). It does not, leaving the return behavior under-specified. The parameter schema is rich, but the overall context lacks important output information that the agent would need.

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 provides 100% coverage with descriptions for both 'mode' and 'expression' parameters. The tool description adds no additional parameter semantics beyond what the schema already provides, so the baseline 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 'Build and parse cron expressions visually' clearly identifies the two primary operations (build and parse) and the resource (cron expressions). This specific verb+resource combination distinguishes it from all sibling tools, none of which target cron 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 clearly indicates usage for building and parsing cron expressions, and there are no sibling tools that overlap, so the use case is well-defined. However, it does not provide explicit when-not-to-use guidance or mention any alternatives, which prevents a perfect score.

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 only states that conversion happens 'in the browser', which is a useful but minimal behavioral detail. It does not disclose output format, file size limits, data handling, or any side effects, leaving significant gaps for the agent.

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

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

The description is a single sentence of 10 words, front-loaded with the core action. Every word earns its place, containing no fluff or repetition. It is appropriately sized for a simple converter tool.

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?

Despite good schema coverage, the tool has no annotations and no output schema, so the description must provide more context. It fails to mention how the conversion works, what the output looks like, or how to handle the two distinct directions and optional parameters. The description is too sparse for a tool with 5 parameters and no structured output guidance.

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 provides 100% coverage for all five parameters with descriptions, satisfying the baseline. The tool description itself adds no additional meaning beyond what the schema already documents, so a baseline score of 3 is appropriate without extra credit.

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 a specific verb 'Convert' and clearly identifies the resource as CSV and Excel (.xlsx), making the tool's purpose immediately clear. It also distinguishes itself from siblings like csv-query or excel-to-pdf by specifying bidirectional conversion between these two formats.

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

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

The description implies the usage scenario (converting between CSV and Excel) but provides no explicit guidance on when to choose this tool over alternatives, nor does it mention exclusions. The 'in the browser' phrase adds minimal context but does not differentiate sibling tools or provide 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 are provided, and the description is a single declarative statement with no mention of side effects, supported SQL dialect, limitations, or reading behavior. It does not disclose what the agent should expect in terms of output or permissions.

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 one sentence, perfectly front-loaded, with no redundant words—ideal for a simple tool. Every word adds value and it is no longer than necessary.

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?

While the tool is simple and schema coverage is 100%, the lack of output schema and absence of any behavioral notes mean the description leaves some ambiguity about return format and SQL feature support. The example query helps, but it's borderline sufficient.

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 already describes both parameters (csv data and query) with 100% coverage, including an example query. The description adds nothing beyond what the schema provides, so baseline 3 applies.

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

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

Description uses specific verb 'Run' with resource 'CSV data' and method 'SQL-like queries', clearly distinguishing it from sibling tools like csv-excel-converter which converts formats. The title and description align perfectly.

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 clearly implies this tool is for executing queries against CSV data, giving context that it's for data retrieval/filtering rather than format conversion. However, it does not explicitly name sibling alternatives or state 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?

With no annotations, the description carries the transparency burden. It discloses that the tool analyzes and presents suggestions, and that it is browser-based, suggesting a non-destructive, local analysis. However, it does not explain how data is handled, what output format looks like, or any limitations, leaving significant behavioral aspects unspecified.

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

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

The description is a single, compact sentence that front-loads the primary action and outcomes, with an informative parenthetical about it being browser-based. Every word earns its place; there is no redundancy or unnecessary detail.

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, parameterless tool, the description is moderately complete but leaves gaps. It does not specify how the article is provided (URL, pasted text, browser context), what the output looks like, or any prerequisites. The lack of annotations and output schema further increases the need for such details, which are missing.

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, so the baseline for this dimension is 4. The description adds value by enumerating the conceptual dimensions being analyzed (CTA placement, link density, read rate), which helps the agent understand what the tool computes even though no explicit parameters 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?

The description clearly states the tool's function: analyzing CTA placement, link density, and read completion rate, then presenting improvement points for conversion rate. It uses specific verbs and resources, and differentiates itself from siblings like sales-writing-analyzer by focusing on these concrete metrics.

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 when one wants to improve an article's conversion rate, and the 'Browser-based tool' note hints at context. However, it provides no explicit when-to-use/when-not-to-use guidance or comparisons to alternative tools, leaving usage largely implied rather than clearly instructed.

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 output formats (JSON/CSV) but does not elaborate on output structure, determinism with seed, or how the format is selected. The schema covers parameters, but the description adds limited behavioral context beyond the basic generation action.

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, front-loaded sentence with no redundant information. It efficiently communicates the core purpose, content types, and output formats in under 15 words, earning it a perfect score for conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no output schema and no annotations, yet the description does not clarify how the output format (JSON vs CSV) is controlled—there is no format parameter in the schema. It also omits any details about return structure or usage context, leaving the agent with ambiguity on how to invoke the tool correctly for a desired format.

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 covers all parameters with descriptions, so the baseline is 3. The description mentions example field types (names, emails, addresses) but does not add meaning beyond what the schema already provides for each parameter. It adds no parameter-specific semantics, so the score remains at the baseline.

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 a specific verb ('generate') and resource ('realistic fake data'), and distinguishes it from siblings by specifying content types (names, emails, addresses) and output formats (JSON/CSV). This is a precise and self-contained purpose statement.

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 offers no guidance on when to use this tool versus alternatives, nor does it mention any exclusionary contexts or prerequisites. It only states what the tool does, leaving the agent to infer appropriate usage without explicit 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 disclosing behavior. It states the core operations but omits any details about assumptions (e.g., business days excludes weekends but not holidays), side effects (none expected), or edge cases like negative amounts for subtraction. For a pure calculation tool, this is a moderate 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 concise sentence of ten words, front-loading the core functionality without fluff. Every word contributes to conveying 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?

The tool has 5 parameters, 2 enums, and no output schema. The description is too terse to clarify parameter relationships, such as which parameters are required for each mode. It also does not hint at return values. There is notable ambiguity: date2 is described only as 'for diff mode', yet business-days counting presumably also requires two dates. This is a significant completeness gap for an agent to invoke the tool correctly.

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

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

Schema description coverage is 100% (every parameter has a description), meeting the baseline of 3. The description itself adds no parameter-level detail beyond the schema's existing explanations. Since the schema already documents mode, unit, date1, date2, and amount adequately, 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 uses specific verbs and resources: 'calculate date differences, add/subtract dates, count business days'. It clearly enumerates three distinct operations, distinguishing it from more specialized siblings like age-calculator or countdown-timer. However, it does not explicitly name any alternative tool or exclusion, so it slightly misses the highest bar for 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 offers no guidance on when to choose this tool over alternatives or how to select among the modes (diff, add, business-days). It does not mention prerequisites, such as the need for two dates in diff/business-days modes or amount+unit in add mode. This is essentially no usage guidance beyond the implied general purpose.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It adds one useful trait—'Browser-based tool'—which explains the lack of parameters, but it does not disclose what happens after generation (e.g., download, preview), whether login is required, or 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?

The description is a single sentence with a parenthetical note, containing no fluff or redundancy. Every word earns its place, and the key information (purpose and browser-based nature) is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter browser-based tool, the description is minimally sufficient, but there is no output schema or explanation of what 'delivery notes with receipt confirmation field' means in practice (e.g., file format, preview vs. download). The description leaves some ambiguity about the tool's workflow.

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, and the description's mention of 'Browser-based tool' clarifies that no inputs are needed. Since the schema is empty, there is no parameter documentation burden, and the description adds the key context of how the tool is invoked.

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: 'Generate delivery notes with receipt confirmation field.' It uses a specific verb and resource, and the term 'delivery note' distinguishes it from sibling tools like invoice-generator and receipt-generator, though it does not explicitly name 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?

No guidance is provided on when to use this tool versus alternatives such as invoice-generator or receipt-generator. The description does not mention typical use cases, prerequisites, or exclusions, leaving the agent to infer when it is appropriate.

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 two calculation methods, but these are already visible in the schema's method enum. It does not explain the output format, how service start date or fiscal year end affect the schedule, or any rounding/calculation conventions.

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

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

The description is a single concise sentence with no wasted words, making it easy to parse. It is not a full grammatical sentence, but it effectively front-loads the core 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?

This is a 6-parameter tool with no annotations and no output schema, so the description must explain more than just the high-level purpose. It fails to describe the return value, how inputs like serviceStartDate and fiscalYearEndMonth influence the schedule, or any other behavior needed for correct invocation.

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

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

Schema description coverage is 100%, so all six parameters are already described in the schema. The description adds nothing beyond what the schema provides, making the baseline score of 3 appropriate.

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

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

The description clearly identifies the tool as producing depreciation schedules using two specific methods, which distinguishes it from sibling calculation tools. However, it lacks an explicit verb like 'calculates' or 'generates,' instead using a noun phrase.

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 use case is implied by the name and description: anyone needing straight-line or declining-balance depreciation schedules. There is no explicit guidance on when to use this tool versus alternatives, nor are any exclusions 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 exist, so the description bears full responsibility for behavioral disclosure. It only says 'side-by-side' comparison, which may imply a visual diff, but the schema shows output can be unified, JSON, or stats. This could mislead users about the actual output formats. No information about limitations, performance, or error handling is provided.

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

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

The description is a single concise sentence with no filler, front-loading the core purpose. It is appropriately sized for a simple tool, though it could include more detail without becoming verbose. No wasted words, but slightly under-specified for completeness.

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 5 parameters and no output schema or annotations, the description is insufficient. It does not mention the configurable output formats, which are important for correct usage. The phrase 'side-by-side' conflicts with the unified format option, leaving users unaware of the tool's full capabilities. The description plus schema cover basic inputs, but the overall behavior and variants are not communicated.

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

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

Schema description coverage is 100%, so baseline is 3. The description does not add any meaning beyond the schema's parameter descriptions. Left/right, format, and label fields are already well documented in the schema, so the description provides no additional 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 states the tool performs diff comparison on text and code, specifically in a side-by-side view. It clearly identifies the resource and action, though it lacks an explicit verb. It distinguishes from siblings by mentioning 'diff', but there is no direct differentiation from similar tools like similarity-checker.

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 usage guidance is provided. The description does not tell when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. With sibling tools like similarity-checker, users might be unsure which comparison tool to choose, but the description offers no clarification.

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

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

With no annotations, the description must carry the full burden of behavioral disclosure. It only adds 'Browser-based tool,' which hints at a client-side UI but does not explain how profit is calculated, what fees are considered, or any 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?

The description is a single, front-loaded sentence that states the core function without any redundant wording. It is appropriately short for the tool's simplicity.

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 parameters and output schema, the description is minimally adequate, but it lacks specifics about which EC platforms are covered, what factors contribute to profit, and any assumptions in the comparison. This could matter when an agent selects among similar 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 tool has zero parameters, so the schema is vacuously complete. The description adds no parameter-related detail, but the baseline for 0 params 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 a specific action (compare) and resource (profits from selling the same product on various EC platforms). It distinguishes itself from sibling platform-specific calculators by focusing on cross-platform comparison.

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

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

There is no guidance on when to use this tool versus the many alternative fee/profit calculators (e.g., rakuten-fee-calculator, shopify-profit-calculator, yahoo-shopping-calculator). The 'Browser-based tool' note only indicates format, not usage context.

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 burden. It discloses that this is a browser-based tool and that output is platform-specific, which is useful. However, it does not explain how the tool behaves once opened, what platforms are supported, or any 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?

The description is a single, front-loaded sentence that states the exact purpose and includes a valuable parenthetical ('Browser-based tool'). Every word adds meaning, with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (0 params, no annotations, no output schema), the description covers the core purpose but omits important context such as which platforms are supported and what the generated output looks like. It is sufficient for basic selection but not 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 tool has zero parameters, so the baseline is 4. The description does not need to explain parameters, and the empty schema is consistent with a browser-based UI tool that requires no direct 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 uses a specific verb '生成' (generate) and a clear resource: EC form texts for purchase thanks, shipping notices, and return handling, differentiated by platform. This distinguishes it from sibling tools like product-description-generator or review-reply-template by clearly scoping the use case.

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 clearly indicates when to use the tool: when generating EC form texts for purchase thanks, shipping notifications, or returns, per platform. It does not explicitly name alternatives or exclusions, but the use context is unmistakable.

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

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

With no annotations, the description carries the full transparency burden. It only mentions 'Browser-based tool' and automatic generation, but does not disclose how the PDF is processed, file handling, privacy implications, limitations, or output format. This is insufficient for a tool that processes sensitive financial 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 a single, concise sentence that front-loads the key action and resources. The parenthetical 'Browser-based tool' is brief and does not detract. Every word adds value, with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no annotations, output schema, or parameters, so the description is the only context source. It clearly states input and output, but omits any prerequisites, limitations, or how the PDF is handled. This is minimally adequate but not fully complete for an AI agent deciding whether to invoke the tool.

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

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

The input schema has zero parameters, so the baseline is 4. The description adds no parameter details, but none are needed. It implicitly assumes the PDF is provided via the browser interface rather than API parameters, which is acceptable given 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 function with a specific verb '自動生成' (automatically generate), naming the source (見積書PDF) and target (経費明細表). It distinguishes itself from sibling tools like expense-report or quote-generator by describing a direct PDF-to-expense-table 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?

The description implies the use case (when you have an estimate PDF and need an expense detail table), but provides no explicit guidance on when to use this tool versus alternatives like expense-report. It lacks exclusion criteria or alternative references.

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

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

No annotations are provided, so the description must disclose behavioral traits. It adds 'Browser-based tool', which implies client-side processing without server upload, but it does not mention potential limitations like file size restrictions, privacy implications, or whether the conversion is irreversible. The added detail is useful but minimal.

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 front-loaded sentence that states the core function and a key behavioral attribute. Every word earns its place, with no fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters and no output schema, the description is largely complete: it specifies input formats, output format, and a behavioral characteristic. It could mention any file size or format edge cases, but for a simple converter, this is sufficient.

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, and the baseline for 0 params is 4. The description does not need to explain parameters, and it does not add any contradictory or extraneous parameter information. The mention of XLSX/CSV inputs provides implicit context about what the tool expects.

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 converts XLSX/CSV files to PDF, using a specific verb ('変換') and explicitly naming the resource and output format. This distinguishes it from sibling tools like word-to-pdf or image-to-pdf, as the target input formats are uniquely identified.

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

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

The description provides no guidance on when to use this tool versus alternatives such as csv-excel-converter or pdf-to-image. It simply states the conversion function without any context about use cases, 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?

No annotations are provided, so the description carries full burden. It discloses the action (strips metadata) and the browser-based nature, which is useful privacy context. However, it does not mention whether the original file is modified, output format, or any limitations, leaving some ambiguity about 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 sentence with a useful parenthetical. Every word contributes to clarity, with no redundancy or 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?

For a parameterless browser-based tool, the description covers the core purpose and privacy context. It could mention output details or explicitly note that it is not for PDFs, but these are not essential for basic 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 input schema has zero parameters, so there is nothing to document. The description doesn't add parameter semantics, but with 0 params the baseline is 4, and it provides no misleading or conflicting 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 uses the specific verb 'Strip' and clearly identifies the resource ('photos') and the data removed ('GPS location, camera info, and metadata'). This distinguishes it from sibling tools like pdf-metadata-remover, which targets PDFs instead of photos.

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

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

The description implies usage for photos that need EXIF removal and adds the context that it is a browser-based tool. It does not explicitly name alternatives or exclusions, but the scope is clear from the word 'photos'.

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

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

With no annotations, the description must disclose behavioral traits, but it only mentions PDF output and being browser-based. It does not explain whether data is stored, if login is required, or any limitations. This is minimal coverage for a tool that presumably handles expense 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 a single sentence with front-loaded key information (category-based, PDF output). Every word earns its place, and the browser-based note is a useful additional constraint.

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 parameters and no output schema, the description is adequate but thin. It tells what output to expect but lacks details on how the tool operates or what input it expects from the user. Given the simplicity, this is a minimum viable description.

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

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

The schema has zero parameters, so the description is not required to detail parameter meaning. The baseline of 4 applies because there are no parameters to clarify, and the description adds a slight bit of context by mentioning 'category-based'.

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 indicates this tool produces category-based expense reports with PDF output, which specifies the resource and output format. It distinguishes from siblings by being the only expense-report relevant tool, though it doesn't explicitly state an action verb like 'create' or 'generate'.

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. While it mentions 'browser-based,' it doesn't explain what user scenarios this addresses or contrast it with other finance/accounting tools in the sibling 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?

No annotations are provided, so the description carries the full burden. It discloses that the tool is browser-based and outlines an interactive workflow (template selection, text input), providing some behavioral context. However, it does not describe output format, delivery method, or any 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?

The description is a single, concise sentence that front-loads the key steps and purpose. Every word contributes meaning, with no fluff 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 (no params, no output schema), the description covers the core purpose and workflow. It could be more explicit about what the final output is and how it is delivered, but for a browser-based tool, it is reasonably 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 tool has zero parameters in the schema, and the baseline for 0 params is 4. The description adds value by describing the user-facing workflow (template selection, text input) that happens in the browser, even though these are not API 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 specifies the tool's function: it generates blog eye-catch images via a template selection and text input flow. The verb 'generates' and resource 'blog images' are specific, distinguishing it from sibling image tools like youtube-thumbnail-maker.

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 workflow implies when to use the tool (creating blog images), but there is no explicit statement of when not to use it or how it compares to alternatives like telop-image-generator or text-overlay-maker. No exclusions or alternative recommendations are provided.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states conversion and lists formats, omitting details about output format constraints, quality semantics, input limitations, or failure modes. An agent cannot anticipate side effects or error conditions.

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, front-loaded sentence with no redundancy. The claim of 11 formats is unsupported by the schema and potentially misleading, which keeps it from a perfect score.

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 conversion tool with no output schema and no annotations, the description lacks critical context about return values, input size limits, format compatibility, or error handling. The schema covers parameter syntax only, not runtime 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?

Schema coverage is 100%, so the baseline is 3. The description adds no parameter meaning beyond the schema; the '11 formats' mention could even confuse expectations about the outputFormat enum, which contains only 6 options.

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 a clear verb ('Convert') and identifies the resource (image formats), distinguishing it from sibling image tools like resizers or compressors. However, it claims support for 11 formats while the schema only lists 6 output formats, creating ambiguity about actual capabilities.

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. Sibling tools such as image-compressor, image-resizer, and pdf-to-image exist, but the description gives no differentiating context or exclusion criteria.

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 available, so the description carries the full burden of behavioral disclosure. It only notes that it is a 'browser-based tool' but does not explain whether it provides estimates, requires user inputs, or what the output represents. The lack of details on limitations or how the calculation works leaves the agent with significant ambiguity.

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, front-loaded sentence that efficiently conveys the core functionality. Every word is necessary, and there is no redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lists the tax categories but does not explicitly state what the tool outputs (e.g., take-home pay after deductions). Since there is no output schema, the description should clarify the result. The title 'フリーランス手取りシミュレーター' partially compensates by implying the output, but the description itself lacks explicit output 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?

Since the tool has zero parameters, the baseline score is 4. The empty input schema clearly signals no parameters, and the description adds no additional parameter information, which is unnecessary in this case.

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 a specific verb ('calculates') and lists the exact tax types (income, resident, business, national health insurance, pension, consumption tax) for freelancers. This distinguishes it from sibling tools that focus on a single tax type, making its purpose unambiguous.

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

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

The description implies use for comprehensive freelancer tax calculation through the phrase '全て計算' (calculates all), but it does not explicitly mention when to choose this over alternatives such as resident-tax-calc or tax-return-calc. No exclusions or alternative references are provided, so guidance is only 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?

With no annotations provided, the description bears the full burden of behavioral disclosure. It mentions 'auto-add' and 'browser-based' but does not explain how the tool operates, whether it modifies existing text, what reading aids are added (furigana, hiragana, etc.), or any side effects. This leaves significant ambiguity for agents deciding on 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 two short sentences with no filler. The first sentence conveys the core action, and the second adds a useful context flag (browser-based). Every word earns its place, and the structure front-loads the most important information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of an output schema and the absence of parameters, the description does not fully explain what the user/agent should expect from the tool. It does not specify input sources, output format, or how the browser-based behavior manifests. Despite its simplicity, the tool is under-specified for an agent to invoke without further clarification.

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 and 100% schema coverage (vacuously). Per the rules, the baseline for 0 params is 4, and the description adds a relevant semantic detail: 'by grade level' implies a configurable level selection, even if not represented as a schema parameter. This gives the agent some idea of what to expect in the browser interface.

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: 'Auto-add reading aids to kanji by grade level.' This uses a specific verb ('add'), a resource ('kanji'), and a distinctive scope ('by grade level'), which differentiates it from the many unrelated sibling tools. The title 'Furigana Adder' is reinforced with meaningful elaboration.

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 given on when to use this tool or when to prefer an alternative. The phrase 'Browser-based tool' gives a vague usage context but does not explain prerequisites, input requirements, or exclusions. There is no mention of scenarios for which this tool is more suitable than others.

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 that the tool is 'Browser-based' and 'instantly' reverse-calculates, but it does not detail the calculation assumptions, required user inputs, or expected interaction flow. This is adequate for a simple calculator but not comprehensive.

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

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

The description is a single concise sentence with a parenthetical note, front-loading the core function with no wasted words. It efficiently communicates the purpose and platform.

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 browser tool, the description is sufficiently complete: it names the output (deduction upper limit) and the platform. It doesn't describe an interaction flow, but the simplicity of the tool and the empty schema make that less critical.

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, so there are no parameter semantics to clarify. The baseline of 4 applies, and the description adds no parameter information because none exist. This 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 states a specific action: 'reverse-calculates the deduction upper limit that keeps self-payment at 2,000 yen.' This clearly identifies the tool's function and differentiates it from sibling tax calculators like resident-tax-calc or tax-return-calc by focusing on the unique furusato tax threshold.

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

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

The description implies the use case (calculating furusato tax deduction upper limit) but does not explicitly state when to use it over alternatives or mention any exclusions. The context is clear enough for an agent to infer, but it lacks direct comparative guidance.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It indicates a pure conversion but does not mention how out-of-range scores are handled, the significance of threshold parameters, or the structure of the returned result. This is minimal for a calculator tool with eight parameters.

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, clear sentence that efficiently conveys the core functionality without unnecessary words. It is front-loaded and immediately understandable.

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 (eight parameters, three required) and no output schema, the description is insufficiently comprehensive. It does not explain the grading algorithm, threshold defaults, or return format, leaving the agent without a clear expected output 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?

Schema description coverage is 100%, with all eight parameters receiving descriptions. The tool description adds no extra parameter semantics beyond the schema, so a baseline score of 3 is appropriate.

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

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

The description clearly states the tool's function: converting three-aspect evaluations into ABC and five-level grades. This specific verb+resource combination distinguishes it from sibling tools like age-calculator or math-evaluator.

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 or how it compares to alternatives. The description implies usage for grading but lacks explicit use cases, 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, the description carries the full burden of behavioral disclosure. It does not mention that hashing is one-way, that the result is returned as a fixed-length string, or that there are no side effects. This lack of behavioral context could leave an agent unaware of important traits.

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

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

The description is a single sentence with no unnecessary words, front-loading the verb and key resource. It is appropriately concise for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple and the schema covers both parameters, but with no output schema or mention of the return value, the description leaves ambiguity about what the agent will receive (e.g., hex string, encoding). It is adequate but not fully complete for a bare description.

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 baseline is 3. The description adds no extra parameter semantics beyond noting algorithms (MD5, SHA-256), which are already listed in the enum. It does not clarify output format or parameter interaction.

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 a specific verb ('Compute') and names concrete hash algorithms (MD5, SHA-256), clearly identifying its purpose. It distinguishes itself from sibling tools like base64-converter or uuid-generator by explicitly referencing hashing.

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 given on when to use this tool vs alternatives, nor any context about prerequisites or suitable scenarios. The description merely states the function without explaining when an agent should choose it over related 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 the full transparency burden. It adds the useful context that this is a browser-based tool, which clarifies execution mode. However, it does not disclose other behavioral details such as how input is provided (e.g., via UI), whether any network calls are involved, or what the output format looks like. It is not misleading but is incomplete.

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, front-loaded sentence that conveys purpose, platforms, and execution context without any filler. Every element earns its place, and the parenthetical 'Browser-based tool' is compact and informative.

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, browser-based generation tool with no output schema, the description covers the essential aspects: what it does, for which platforms, and how it runs. While it doesn't detail the user interaction flow, the simplicity of the tool makes this level of description sufficient. It is not overburdened with unnecessary information.

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, so the baseline is 4. The description conceptually mentions 'keywords' as the input, which adds semantic meaning beyond the empty schema. There is no parameter list to elaborate, so this 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 that the tool generates SNS hashtags from keywords, and explicitly names supported platforms (TikTok/Instagram/X), which distinguishes it from sibling tools like youtube-tag-generator. The verb '自動生成' (auto-generate) plus resource 'ハッシュタグ' makes the purpose unambiguous.

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

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

The description provides clear context for when to use the tool: when needing hashtags for TikTok, Instagram, or X. It does not explicitly mention alternative tools or when not to use it, but the platform limitation is a strong contextual guide. Since no alternatives are named, it doesn't quite reach the 'explicit when/when-not' bar.

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 disclosing behavior. It states that dangerous tags and attributes are removed, but does not explain what 'dangerous' means, how the 'level' parameter affects behavior, whether content is preserved outside those tags, or what the output looks like. Significant behavioral details are missing.

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

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

The description is a single concise sentence that is front-loaded with the main action. Every word earns its place; there is no fluff 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?

The tool has three parameters with an enum and no output schema or annotations. The description provides a high-level purpose but does not explain sanitization levels, empty-element removal, or return format. A bit more context would be useful, but the schema fills in parameter details, making it minimally adequate.

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 fully documents all three parameters (html, level, removeEmpty) with descriptions, so the baseline is 3. The tool description adds no additional meaning beyond the schema—it only mentions 'dangerous tags and attributes,' which relates to the 'html' parameter but does not enrich understanding of 'level' or 'removeEmpty'.

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 a specific verb ('Sanitize') and resource ('HTML') and states the exact action ('removing dangerous tags and attributes'). This clearly distinguishes the tool from siblings, none of which are sanitizers.

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 purpose is self-evident, implying usage for cleaning HTML, but there is no explicit guidance on when to use vs. alternatives, prerequisites, or exclusions. It does not name any alternative or say 'use when...'.

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 only adds 'Browser-based tool', which implies some rendering context, but does not disclose how input is provided, output format details, limitations, or any side effects. This is a minimal gesture toward 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 one short sentence, front-loaded with the core function, and includes no filler or redundant content. It is appropriately sized for a zero-parameter tool.

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?

Despite being a simple tool, the description omits essential context: how HTML content is supplied, what the output PDF contains, and any browser-specific behavior. Given the abundance of sibling PDF tools and the lack of output schema/annotations, this description is incomplete.

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, so the baseline score is 4. The description does not need to explain parameter details since none exist, and the schema coverage is trivially 100%. No conflict arises.

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 a specific verb and resource: 'HTMLをPDFに変換' (convert HTML to PDF). This clearly distinguishes it from sibling tools like excel-to-pdf, word-to-pdf, and image-to-pdf, making the purpose unambiguous.

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 such as other conversion tools. It only mentions 'Browser-based tool', which hints at context but does not offer exclusions or alternative suggestions.

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 burden of behavioral disclosure. It states the return payload but does not mention that it performs a network request, that the default followRedirects=false shows redirect targets rather than following them, or any potential side effects/timeouts. The schema covers some of this, but the description alone is thin.

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

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

A single sentence that is direct and informative, listing the key outputs without extraneous wording. It earns its place and is immediately scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple tool and full schema coverage, the description covers the essential return values. It lacks explicit error behavior or examples, but the output list is sufficient for an agent to know what to expect. No output schema exists, so the description's list is valuable.

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 each parameter already well-described (url format, method enum, timeout bounds, followRedirects semantics). The tool description adds no additional parameter context, so it stays at the baseline of 3.

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 a specific verb ('Probe') with a clear resource ('a URL') and enumerates the exact return data (status code, headers, response time, redirect info). This fully distinguishes it from any sibling tool, none of which probe URLs.

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 purpose is clear, and there are no sibling tools that serve the same function, so the intended use case is evident. However, there is no explicit guidance on when to choose this tool over alternatives (which are not needed) or any conditions like using GET for body info, though that hint exists in the schema.

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 disclosure burden and clearly states key behavioral traits: no server upload and browser-based processing. This provides meaningful privacy-related context beyond the empty input schema, though it does not cover output format or 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?

The description is a single, front-loaded sentence with no filler. Every word adds value: the purpose, the privacy guarantee, and the delivery mechanism.

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 (no params, no output schema, no annotations), the description covers purpose and key behavioral context. It could mention output or limitations, but for a zero-parameter browser tool the information is largely sufficient.

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 and the schema coverage is trivially 100%. The description adds no parameter details but none are needed, so the baseline of 4 applies.

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

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

The description uses a specific verb ('Create') and resource ('passport/ID photos'), clearly distinguishing it from sibling tools like general image editors or calculators. It states exactly what the tool produces.

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

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

The description implies the tool should be used when a user needs passport/ID photos and values privacy, but it does not explicitly mention alternatives or when not to use it. There is no comparison or exclusion phrasing like 'use X instead'.

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

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

With no annotations, the description carries the full burden of disclosing behavior. It mentions 'AI auto-correction' and 'Browser-based tool,' which indicate an automatic, client-side process. However, it does not explain how the input photo is provided (e.g., upload), whether the original is preserved, output format, or any limitations. This lack of functional detail leaves significant ambiguity.

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 core sentence plus a brief parenthetical. Every word earns its place. 'AI auto-correction for dark or underexposed photos' is front-loaded and informative. The 'Browser-based tool' note adds contextual value without unnecessary 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 the tool's simplicity (0 params, no output schema), the description conveys the essential purpose. However, it is incomplete in explaining the input mechanism: how the agent or user designates which photo to adjust. Since there are no parameters, the description should clarify that the tool operates via browser UI or on a currently selected image. This missing input-handling detail prevents a higher score.

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, so the schema is trivially complete. The description adds no parameter-level detail, which is acceptable given there are none. Baseline for 0 params is 4, and the description does not hinder understanding of how to invoke the tool, though it could have clarified that no explicit parameters are needed and input is likely provided through browser interaction.

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: 'AI auto-correction for dark or underexposed photos.' This is a specific verb (correct) and resource (photos) with a clear scope (dark/underexposed). It distinguishes itself from sibling image tools like image-crop, image-resizer, and bg-remover by focusing on brightness adjustment.

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

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

The description implies usage for dark or underexposed photos but provides no explicit guidance on when to use this tool versus alternatives. It does not mention exclusions or prerequisites. The phrase 'AI auto-correction' suggests an automatic process, but no direct comparison with 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 adds useful context by noting it is a 'Browser-based tool' and explains the core operation, but it does not disclose limitations, privacy implications, output format, or expected behavior after 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 a single, front-loaded sentence with a useful parenthetical note. Every word adds value, and there is no redundancy or 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?

For a simple zero-parameter browser tool, the description gives a clear purpose and indicates the operating context. However, with no output schema or annotations, it leaves gaps about what the user will see, how photos are provided, and any constraints on photo count or formats.

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 is empty with zero parameters, so there are no parameter semantics to explain. The description appropriately focuses on the task itself rather than parameters, matching the baseline for 0-param 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 function with a specific verb and resource: 'Combine multiple photos into a single image with layout templates.' This distinguishes it from sibling image tools like image-crop or image-resizer.

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

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

The description provides clear context for when to use the tool—when a user wants to combine multiple photos into a single collage. However, it does not explicitly mention when not to use it or name alternative 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. It notes the tool is 'browser-based' and mentions features (eyedropper, palette extraction), but does not disclose limitations, input method, output format, or whether any server-side processing occurs. This is acceptable but not thorough.

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

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

The description is a single compact sentence, followed by a useful parenthetical about being browser-based. It contains no fluff and every phrase adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple with no parameters, but no output schema exists, so the description should clarify what the user gets (e.g., hex codes, RGB values, palette format). It mentions 'palette extraction' but does not describe the return format, leaving some ambiguity.

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, so a baseline of 4 is appropriate. The description does not need to document parameter syntax, and it correctly focuses on the tool's behavior rather than nonexistent 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 clearly states the tool identifies colors from images using an eyedropper and automatic palette extraction. It distinguishes itself from siblings like color-converter and color-palette by specifying the input (image) and the action (identify colors).

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 'from images' gives clear context for when to use this tool, implying it is for picking colors from existing images rather than generating palettes from scratch. However, it does not explicitly mention alternatives or when not to use it, so it falls short of a 5.

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 that processing happens in the browser (implying local/no-upload) and mentions the target-size feature. However, it does not describe output format, quality preservation, or file-handling behavior, leaving some behavioral aspects unspecified.

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

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

The description is a single, compact sentence that conveys purpose, supported formats, context, and a key capability. It contains no unnecessary words, and the bilingual structure is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

As a zero-parameter, browser-based utility with no output schema, the description covers the core behavior and a notable feature. It omits details like how results are delivered, but given the tool's simplicity, the description is adequately 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 zero parameters, and the description adds no parameter-level details. Per the baseline for 0-param tools, this is acceptable; the mention of '目標サイズ指定' (target size specification) is a tool feature rather than an input parameter.

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 action (軽量化 = compress/reduce size) applied to specific image formats (JPG/PNG/WebP), and adds the context of browser-based processing. This distinguishes it from sibling tools like image-resizer or image-crop, making the purpose unambiguous.

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 establishes when to use the tool: for compressing JPG/PNG/WebP images in the browser, with optional target-size control. It does not explicitly name alternatives or exclusions, but the given context is clear enough for selection among many image-related 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 provided, the description carries full responsibility for behavioral disclosure. It reveals the interaction model (drag-to-select, preset ratios) but omits critical context such as output format, whether the original image is modified, persistence, or system requirements. This is a significant gap for a tool that likely manipulates images.

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 terse phrases that convey the core functionality. Every word contributes meaning, and it is appropriately front-loaded with the key verb ('cropping') and interaction model.

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, interactive browser tool with no parameters and no output schema, the description is relatively complete. It communicates what the tool does and how the user interacts with it. However, it could benefit from a sentence about what the crop output is or how to retrieve the result, so it is not perfect.

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, so the baseline is 4 per the rubric. The description adds value by clarifying that the tool is browser-based and interactive, which explains why no server-side parameters are needed. No additional parameter details are possible 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?

The description clearly states the tool performs cropping via drag-to-select with preset aspect ratios, giving the specific verb and resource. It distinguishes itself from related tools like image-resizer or smart-resize by specifying cropping and the browser-based interaction, though it does not explicitly name 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 only usage signal is the phrase 'Browser-based tool,' which implies user interaction but does not explain when to choose this tool over other image editing tools. There is no explicit when-to-use, when-not-to-use, or mention of alternatives, leaving the agent without clear guidance on tool selection.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It states the core behavior (resize to exact dimensions, aspect ratio lock) but does not mention output format, whether the original is modified, how fit modes behave, or any side effects. The schema fills some gaps, but the description alone 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, front-loaded sentence that communicates the essential function without any filler. It is concise and appropriate for a simple utility tool with a well-documented 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?

The tool has no output schema, and the description does not mention what the tool returns (e.g., base64 image, file path) or how it handles the fit modes. It also lacks any reference to sibling tools or usage context. Given the descriptive schema compensates for parameters, the description is still incomplete for an agent to fully understand the tool's behavior and integration.

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

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

Schema description coverage is 100%, and the parameter descriptions in the schema are fairly clear (e.g., 'Target width in pixels'). The description adds 'exact pixel dimensions' and 'aspect ratio lock' which loosely map to width/height and fit, but it doesn't add any new semantic detail 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 'Resize images to exact pixel dimensions with aspect ratio lock' clearly identifies the specific operation (resize) and resource (images), and adds a distinctive behavioral trait (aspect ratio lock). This distinguishes it from siblings like image-crop or image-compressor, which have 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 gives no guidance on when to use this tool versus alternatives like smart-resize or image-crop. It does not mention exclusions, prerequisites, or context, 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.