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 discloses a key behavioral trait: the entry is created with status 'in_progress'. It also hints at the lifecycle by referencing journal_finalize_entry. However, it does not mention auth requirements, error conditions, or return format, which would increase transparency further.

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

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

Two sentences, front-loaded with the action, then a crucial lifecycle note and a pointer to the sibling tool. Every sentence earns its place 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 is simple (one required parameter), and the schema covers all parameter semantics. The description adds valuable lifecycle context (in_progress status, finalize step) that is not present in the schema. Lacking an output schema, it does not describe return values, but that is not critical for a create tool.

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

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

Schema coverage is 100%, and each parameter has a clear description in the schema. The tool description adds no additional parameter-level meaning 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 uses a specific verb and resource: 'Create a new journal entry in JournalOwl.' It also states the initial status ('in_progress') and explicitly differentiates from the sibling tool journal_finalize_entry by directing users to it for completion.

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 states when to use this tool (to create an entry) and provides an explicit alternative for a different step (use journal_finalize_entry to generate AI analysis and complete the entry). This gives clear 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 carries the full burden of behavioral disclosure. It adds meaningful context by disclosing that the tool generates sentiment analysis, themes, and insights, and imposes a minimum character requirement. It does not mention potential side effects like making the entry read-only or whether the analysis is asynchronous, but the provided details go beyond a simple restatement.

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 compact: two sentences delivering all essential information without redundancy. It front-loads the primary action and then clarifies the analysis components and the length constraint, every sentence 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?

Despite the lack of an output schema, the description adequately conveys the tool's purpose and expected outputs (sentiment, themes, insights). It does not fully describe the return structure or failure behavior (e.g., what happens if the entry is too short), but for a single-parameter tool, the description 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 schema already has 100% coverage for the single parameter entry_id, describing it as 'The ID of the journal entry to finalize'. The description adds no additional parameter-level detail, which is acceptable given the simplicity and high schema coverage. 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 ('finalize') with a clear resource ('journal entry') and states the main outcome ('generate AI analysis'). It distinguishes this from sibling tools like create/list/get/search by emphasizing the finalization and analysis generation aspect.

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 a clear prerequisite ('Entry must have at least 100 characters'), implying that it should be used only for entries meeting that length. However, it does not explicitly state when not to use this tool or name alternative tools like journal_get_weekly_review for broader analysis.

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 response includes AI analysis and insights, which is useful behavioral context. However, it does not mention error behavior, authorization needs, or any side effects, though the verb 'Get' implies 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, front-loaded sentence that directly states the action and key context without any wasted words. It is concise and immediately 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 simple GET-by-ID tool with two parameters and no output schema, the description covers the main return content (the entry) and the optional analysis. While it lacks error-case details, the overall context is sufficient given the tool's low complexity and sibling context.

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

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

Schema coverage is 100%, so the parameters are already documented. The description adds context about AI analysis, which aligns with the include_analysis parameter, but does not provide additional syntax or format details. Baseline 3 is appropriate given the schema handles 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 action ('Get'), the specific resource ('a specific journal entry'), and the method ('by ID'), which distinguishes it from sibling tools like list_entries and search. It is a specific verb+resource+scope construction.

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

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

The description provides no explicit when-to-use or exclusions, only implying via the name that it is for fetching a single entry by ID. It does not mention alternatives like list_entries or search, leaving the agent to infer the appropriate use case.

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 clearly identifies this as a read-only get operation (via 'Get') and describes the content returned, but it does not disclose any additional behavioral traits such as prerequisites, rate limits, or whether the review is computed on demand versus stored. It provides minimal context beyond what the name already implies.

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 short sentences convey the purpose and the key parameter hint without waste. No redundant or verbose wording.

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 a single parameter and no output schema. The description explains the high-level output (summary of activity, emotional trends, insights) but does not specify the output format or any edge cases. Given the tool's simplicity and full schema coverage, it is adequate though not exhaustive.

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 'week' parameter. The description's 'Use "latest" to get the most recent review' restates what the schema already says, adding no new semantic value. Baseline 3 is appropriate 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 uses the specific verb 'Get' with the resource 'weekly review' and explicitly mentions what it summarizes (journaling activity, emotional trends, insights), clearly distinguishing it from sibling tools like journal_get_entry or journal_get_writing_style.

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 a user wants an aggregated weekly summary rather than individual entries, but it does not explicitly state when to use this over alternatives or provide exclusions. The only usage hint given is the 'latest' parameter value, which is about parameter selection rather than 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the action of getting a style without mentioning whether it is read-only, what it returns, or any side effects. This is minimal disclosure, barely beyond the tool name.

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 conveys the tool's purpose without any redundant language. It is perfectly concise and 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 tool with no parameters and no output schema, the description sufficiently communicates what the tool returns (writing style, tone, suggestions). It is complete enough for a simple getter, though it could optionally mention that the response is personalized.

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 since there are none, and it stays silent on them, which 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 ('Get') and names a distinct resource ('user's preferred writing style, tone, and personalized journaling suggestions'). This clearly differentiates it from sibling tools that focus on journal entry creation, retrieval, or 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 does not explicitly state when to use this tool or mention alternatives. However, the resource 'writing style' implies it should be used when you need the user's stylistic preferences, which is contextual but not explicitly guided.

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. It implies a read operation ('List') and filter capabilities, but does not disclose behavioral details like ordering, pagination behavior, tag matching semantics, or any authentication requirements. It adds some context but not rich behavioral disclosure.

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

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

Two short, front-loaded sentences: the first states the main action, the second summarizes filter capabilities. No redundant words; every sentence earns its place.

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

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

For a simple read-only list tool with fully documented optional parameters, the description covers the core purpose and filter categories. There is no output schema, so explaining return format is unnecessary. Missing explicit pagination guidance, but the schema already defines limit and offset.

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 a helpful grouping of filters (date, status, tags) that maps to the schema, but it does not add meaning beyond what each parameter description already provides.

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

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

The description uses a specific verb ('List') with a clear resource ('journal entries') and source ('JournalOwl'), and mentions filter dimensions. It does not explicitly compare with siblings like journal_get_entry or journal_search, but 'list' vs 'get' vs 'search' is inherently distinguishing enough.

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 states the tool is for listing journal entries and using filters by date, status, or tags, conveying the main use case. However, it does not mention when to prefer this over journal_search or journal_get_entry, nor does it include exclusion cues.

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

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

No annotations are provided, so the description must disclose behavior. It conveys the core behavior (search by text) and implies a read-only operation, but it does not describe the return format, matching semantics (e.g., substring vs. semantic), or result ordering. This is a basic disclosure without deeper 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—two sentences. The first sentence front-loads the main verb and resource; the second adds illustrative examples 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?

For a simple 2-parameter search tool with full schema coverage, the description provides sufficient context for an agent to understand the tool's purpose and invoke it. The absence of an output schema is partially offset by the phrase 'find entries,' which implies a list of matching entries. Minor gaps like result format are not critical for selection and 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?

Both parameters (query, limit) have descriptions in the schema, achieving 100% coverage. The description does not add extra semantics beyond the schema, so the baseline score of 3 applies.

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

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

The description clearly states the action ('Search') and resource ('journal entries') with a specific method ('by text'). It also expands on the kinds of search intents (topics, emotions, events). This distinguishes it from sibling tools like journal_list_entries or journal_get_entry.

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 finding entries by text but does not explicitly state when to prefer this over listing all entries or getting a specific entry. No exclusions or alternative tool 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.