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 describes the key behavior of appending to existing entries for today, which is valuable context beyond basic 'add' functionality. However, it lacks details on permissions, error handling, or file storage specifics, leaving gaps for a mutation tool.

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

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

The description is two sentences that are front-loaded with the core purpose and include essential behavioral context (appending rule). Every word earns its place with no redundancy or fluff, making it highly efficient.

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

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

For a mutation tool with no annotations and no output schema, the description provides adequate purpose and key behavior (appending). However, it lacks details on return values, error cases, or system constraints, which would be needed for full completeness given the complexity.

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

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

Schema description coverage is 100%, so the schema already fully documents the two parameters (content and tags). The description does not add any parameter-specific details beyond what the schema provides, such as format examples or usage tips, resulting in the baseline score 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 clearly states the specific action ('Add a new journal entry') and the resource ('journal entry'), distinguishing it from sibling tools like get_entry_by_date (retrieval) or search_entries (search). It also specifies the unique behavior of appending to existing entries for today, which further differentiates its 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 clear context for when to use this tool: for adding new journal entries, with the specific rule that if an entry for today exists, it appends instead of creating a new one. However, it does not explicitly state when not to use it or name alternatives (e.g., using get_entry_by_date to check first), which prevents a score of 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 of behavioral disclosure. It states what the tool does but doesn't reveal behavioral traits like whether it's read-only, requires authentication, has rate limits, or what the summary includes. For a tool with zero annotation coverage, this is a significant gap in transparency.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

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

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

Given the complexity (a summary tool with no output schema and no annotations), the description is incomplete. It doesn't explain what 'summary statistics' entail, how data is aggregated, or what the return format looks like. For a tool that likely outputs structured data, this leaves significant gaps for the 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?

The tool has 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description doesn't add param semantics, but with no parameters, the baseline is high. It could slightly improve by noting the lack of inputs, but it's already 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 verb ('Get') and resource ('summary statistics for journal entries'), making the purpose understandable. However, it doesn't differentiate from siblings like 'get_recent_entries' or 'get_entry_by_date' in terms of what makes this summary unique, which prevents a perfect score.

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

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

No guidance is provided on when to use this tool versus alternatives such as 'get_recent_entries' or 'get_entry_by_date'. The description implies usage for summary statistics but lacks explicit context or exclusions, leaving the agent to infer based on tool names alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get journal entry' but doesn't describe what happens if no entry exists for the date (e.g., returns null, error, or empty response), authentication requirements, rate limits, or return format. This leaves significant gaps for a tool that likely interacts with data storage.

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 purpose ('Get journal entry for a specific date') with zero wasted words. Every part of the sentence contributes directly to understanding the tool's function, making it appropriately sized and well-structured.

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

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

Given the lack of annotations and output schema, the description is incomplete for a data retrieval tool. It doesn't explain return values (e.g., entry content, metadata, or error cases), behavioral traits like idempotency, or how it differs from siblings. For a tool with one parameter but potential complexity in data access, more context is needed.

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

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

The input schema has 100% description coverage, with the 'date' parameter fully documented in the schema as 'Date in YYYY-MM-DD format'. The description adds no additional parameter semantics beyond implying the date is used to fetch a specific entry, so it meets the baseline for high schema coverage without compensating value.

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

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

The description clearly states the verb ('Get') and resource ('journal entry') with specific scope ('for a specific date'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'get_recent_entries' or 'search_entries' that might also retrieve entries, which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'get_recent_entries' or 'search_entries'. It mentions 'specific date' but doesn't clarify if this is for exact date matching only or if there are edge cases (e.g., no entry exists for that date). No explicit when/when-not instructions or prerequisites are included.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It doesn't specify whether this is a read-only operation (implied by 'Get' but not explicit), what format the entries are returned in, whether there's pagination, authentication requirements, or rate limits. For a retrieval tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is a single, straightforward sentence that efficiently conveys the core functionality without unnecessary words. It's appropriately front-loaded with the main action and resource. However, it could be slightly more informative by adding context about ordering or default behavior, though this doesn't significantly detract from its conciseness.

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

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

Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what 'most recent' entails (e.g., sorted by date, time-based cutoff), the structure of returned entries, or error conditions. For a tool that likely returns multiple data objects, more context is needed to guide the agent effectively, especially with sibling tools offering alternative retrieval methods.

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

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

The schema description coverage is 100%, with the single parameter 'limit' fully documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema (e.g., it doesn't clarify what 'most recent' means in terms of ordering or time range). This meets the baseline score of 3 when the schema adequately covers 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 action ('Get') and resource ('most recent journal entries'), making the purpose immediately understandable. It distinguishes from siblings like 'get_entry_by_date' (date-specific) and 'search_entries' (keyword-based), though it doesn't explicitly mention these distinctions. The description is specific enough to understand what the tool does without being tautological.

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 like 'get_entry_by_date', 'get_daily_summary', or 'search_entries'. It doesn't specify scenarios where retrieving recent entries is preferable to other retrieval methods, nor does it mention any prerequisites or constraints for usage. The agent must infer usage context from the tool name alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists tags with usage counts, implying a read-only operation, but doesn't cover aspects like pagination, sorting, error conditions, or whether it requires authentication. 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 a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

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

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

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate as a minimum viable explanation. However, it lacks details on behavioral traits like response format or error handling, which would be helpful even for a simple tool, keeping it from 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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately adds no parameter details, and the baseline for 0 parameters is 4, as it doesn't need to compensate for any schema gaps.

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

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

The description clearly states the verb ('list') and resource ('tags used in journal entries'), and specifies the scope ('all tags' with 'usage counts'). However, it doesn't explicitly differentiate from sibling tools like 'search_entries' which might also involve tags, so it doesn't reach the highest score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'search_entries' or 'get_recent_entries' that might also retrieve tag-related information. It lacks explicit when/when-not instructions or named alternatives, leaving usage context implied at best.

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 searchable criteria but doesn't describe important behaviors like whether this is a read-only operation, what the return format looks like, whether results are paginated, or any performance considerations. For a search tool with 6 parameters, this leaves significant gaps in understanding how it behaves.

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

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

The description is extremely concise at just 9 words, front-loading the core functionality without any wasted words. Every element ('Search journal entries by date range, tags, or keywords') directly contributes to understanding the tool's purpose.

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

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

For a search tool with 6 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns, how results are structured, whether it's paginated, or any behavioral constraints. The agent would need to guess about important aspects of tool behavior and output.

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

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

The description mentions three search criteria (date range, tags, keywords) which map to some of the 6 parameters. However, with 100% schema description coverage, the schema already fully documents all parameters including 'limit' and 'offset'. The description adds minimal value beyond what's already in the structured schema, meeting the baseline for high schema coverage.

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

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

The description clearly states the tool's purpose as 'Search journal entries by date range, tags, or keywords', which includes a specific verb ('Search') and resource ('journal entries'). It distinguishes from some siblings like 'add_entry' (creation) and 'list_tags' (metadata listing), but doesn't explicitly differentiate from 'get_recent_entries' or 'get_entry_by_date' which might also retrieve entries.

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 like 'get_recent_entries' or 'get_entry_by_date'. It mentions searchable criteria but doesn't indicate when this search capability is preferred over simpler retrieval methods, nor does it mention any prerequisites or exclusions.

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