HelloTime MCP

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

No annotations exist, so description bears full burden. It does not disclose whether the operation is read-only, any side effects, authentication needs, or response format.

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

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

Single sentence with clear action and listing. Efficiently front-loaded with purpose.

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

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

Given no output schema, description lacks details on return structure (e.g., format of features/currency/positioning). Adequate for a simple tool but could be more 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?

Schema description coverage is 100% and already explains the parameter (ISO code, omit for full matrix). The description redundantly lists country codes but adds no new semantic context.

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

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

The description clearly states the tool returns per-country features, default currency, and product positioning, and lists supported countries. It distinguishes from sibling tools like feature_search or list_competitors.

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

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

No guidance on when to use this tool versus siblings; no when-not or context provided. Sibling tools are listed but not compared.

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

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

No annotations provided, so description carries full burden. Declares it is a search and returns results near the top, but lacks disclosure on side effects, authorization needs, error behavior, or result format. Insufficient behavioral detail for a search 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?

Two sentences: first states purpose clearly, second provides illustrative examples. No redundant information, efficiently 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?

Adequate for a search tool given examples, but lacks details about return structure or pagination. No output schema; description could clarify result format. Sibling context helps situate it, but completeness is average.

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

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

Schema covers 100% of parameters with descriptions. The description adds example queries but does not significantly enhance meaning beyond the schema. 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?

Clearly states it performs free-text search across multiple feature domains (plans, products, countries, payroll, etc.) and provides specific query examples. Differentiates from sibling tools like list_features by being a cross-domain search.

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

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

Implies usage through examples (e.g., queries like 'PF rate', 'vs Truein'), but does not explicitly state when to use this tool versus sibling tools like list_features or country_support. No when-not or alternative instructions.

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

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

With no annotations provided, the description fully bears the burden of behavioral disclosure. It clearly states the output format (competitor entries with wins and pricing notes) and the optional filter parameters. No side effects or hidden behaviors are implied, and the description is consistent with a read-only operation.

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

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

The description is a single, well-structured sentence that immediately states the tool's purpose and lists the competitors. It is concise with no unnecessary words or repetition.

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

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

For a simple list tool with no output schema, the description provides sufficient context by explaining the main output (wins and pricing notes) and optional filters. It could be slightly more detailed about the exact fields in each entry, but it is adequate for an agent to understand the tool's functionality.

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 already provides 100% description coverage for all three parameters (id, tier, country) with enums and context. The description's mention of optional filters adds no new semantic information beyond what is in the schema, thus meeting the baseline for high 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 explicitly states it returns competitor positioning entries with specific content (where HelloTime wins, where the competitor wins, pricing notes) and lists the competitors (Truein, Deputy, etc.). It is clearly distinct from sibling tools like list_features or payroll_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?

The description does not provide explicit guidance on when to use this tool instead of alternatives like feature_search or list_features. It only states the function and optional filters, leaving the agent to infer usage context. No alternatives or exclusions are mentioned.

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

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

With no annotations, the description carries full burden. It does not disclose read-only nature, authentication needs, rate limits, or side effects. It only lists features without 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?

Single sentence, front-loaded with purpose. The list of features is somewhat long but not excessive. No wasted words.

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

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

No output schema and description does not explain return format or how filters interact. Given sibling tools exist, more context would help the agent decide.

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 baseline 3 applies. The description lists feature categories but adds no extra meaning beyond the schema's enum and descriptions.

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

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

The description clearly states the tool lists HelloTime features and provides a comprehensive list of feature categories. However, it could more precisely define what 'features' entail (e.g., names, descriptions, availability).

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

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

No guidance on when to use this tool versus siblings like feature_search or list_plans. The description does not mention prerequisites or fallback scenarios.

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

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

With no annotations, the description provides behavioral context: it lists plans, notes permanent free tier for small teams, and mentions 7-day trial for paid tiers. This covers key traits, though it could explicitly state it is read-only and has no side effects.

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

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

Two sentences: first summarizes purpose and what is included, second adds key details about free tier and trial. No wasted words, front-loaded 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 no output schema, the description explains what is returned (prices, discounts, trial info) but does not detail the exact structure. Sufficient for an agent to decide, but could be more explicit about the response 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?

Both parameters (plan and country) have enum descriptions in schema. The description adds meaning by listing specific plan names and mentioning volume/annually prepay discounts not in schema. It enriches parameter understanding.

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

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

The description states it lists HelloTime pricing plans with specific details (prices, discounts, free trial). It clearly distinguishes from siblings like feature_search or country_support by focusing on pricing.

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 getting pricing info but does not explicitly state when to use this tool versus alternatives like list_features for feature details or country_support for country-specific info. No 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 are provided, so the description carries full responsibility. It discloses the return fields (rail, use-cases, issuing authority, etc.) and filtering behavior. For a read-only list tool, this is sufficient; no contradictions.

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

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

The description is a single paragraph that front-loads the core purpose. It includes many examples which are helpful but slightly verbose; still concise overall.

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 the tool has 4 optional parameters, no required parameters, and no output schema, the description adequately explains the return fields and filtering. The context signals confirm high schema coverage, leaving no 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 already covers all 4 parameters with descriptions (100% coverage). The description adds context about filtering but does not significantly enhance meaning 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 uses specific verbs ('list') and a clear resource ('local bank-rail / wallet payment methods') with concrete examples. It distinguishes itself from sibling tools like 'country_support' and 'feature_search' by focusing on payment methods.

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

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

The description implies usage context ('relevant to HelloTime payroll and contractor payouts') and mentions filtering options. However, it lacks explicit when-not-to-use guidance or direct comparison to alternatives.

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

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It correctly identifies the tool as a read-only query returning data and status, but lacks details on auth requirements, rate limits, or side effects. No contradictions exist.

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

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

The description is a single, well-structured sentence that front-loads the purpose and includes illustrative examples. Every word earns its place, with no redundancy or extraneous information.

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

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

Given the tool's simplicity (one parameter, no output schema), the description adequately explains what the tool returns and its status. However, it could be more complete by specifying error handling or the format of the return value beyond examples.

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 the 'country' parameter having a clear enum and description. The description adds output context but does not enhance parameter meaning beyond what the schema provides, meeting the baseline expectation.

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

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

The description clearly states the verb 'return' and the resource 'supported payroll engines' with concrete examples (e.g., AU STP2 + super). It distinguishes itself from sibling tools like 'country_support' and 'list_features' by focusing specifically on payroll engines per country.

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 siblings like 'feature_search' or 'statutory_rates'. It does not mention prerequisites, contexts, or alternatives, leaving the agent to infer appropriateness.

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 discloses that India block is internally-reviewed while AU and US entries are public-source-unreviewed, and mentions verification filter. This adds value beyond the schema, though it could note rate limits or response structure.

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

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

The description is two sentences: first states purpose and returned fields, second lists filter options. It is concise and front-loaded, with no wasted words. Room for slight improvement in structure (e.g., bullet points) but adequate.

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

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

Given no output schema, the description lists four key fields (rate, ceiling, slab, authority, verification status). With 7 optional parameters and no required ones, it covers the main context for usage. It does not mention pagination or limits, but is sufficient for a query tool.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds context like case-insensitive substring match for state and scheme, and explains verification enum values. This improves parameter understanding beyond the schema.

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

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

The description clearly states 'Return statutory payroll-rate entries with rate, ceiling, slab, authority, and verification status.' This is a specific verb+resource combination that distinguishes it from sibling tools like country_support or feature_search.

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

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

The description implies usage for looking up payroll rates with various filters, but does not explicitly state when to use this tool over alternatives or provide any exclusions. The sibling tools are different enough that confusion is unlikely, but explicit guidance is missing.

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