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

No annotations provided, so description carries full burden. It discloses the side effect of writing a decision event and mentions underlying policy/memory, but does not detail whether the tool is safe, idempotent, or has destructive potential.

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 efficient sentences with no fluff. The first sentence states the core function, the second adds a key side effect. Well structured for quick 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 tool with 7 parameters and no output schema, the description provides only the high-level purpose. It does not explain allowed values, return format, or how to interpret the four possible outcomes (allowed, blocked, risky, warns), leaving gaps 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 0% and the tool description provides no details about the 7 parameters (e.g., meaning of 'now', 'date', 'players', etc.). The description fails to compensate for the lack of 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 checks booking status (allowed, blocked, risky, warns) and mentions writing a decision event. However, it could better distinguish itself from sibling 'write_decision_event' by clarifying that its primary purpose is checking, not just writing.

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

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

No explicit guidance on when to use this tool vs alternatives. With siblings like 'create_soft_hold' and 'check_pricing_action', the description fails to clarify that this is for checking policy compliance before a booking action.

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

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

With no annotations provided, the description carries full burden. It states that the tool writes a decision event, which is a side effect, but does not disclose other behavioral traits such as error conditions, rate limits, or required permissions. The description is adequate but could be more 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 concise with two sentences, but the first sentence is somewhat dense listing many factors. It could be slightly more focused, but overall it is not overly verbose.

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 6 parameters, no output schema, and no annotations, the description lacks important details such as what the return value is, any constraints on input formats, and preconditions for use. It is incomplete for an agent to invoke 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 schema description coverage is 0%, meaning the schema properties have no descriptions. The tool's description mentions criteria like 'absolute floor' and 'discount limits' but these are not parameters; the actual parameters (date, agentId, courseId, etc.) are not explained. The description adds minimal value beyond the raw 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 checks whether a quoted or discounted price is allowed, specifying several criteria. It also mentions that it writes a decision event, but does not explicitly differentiate it from the sibling tool 'write_decision_event' which may cause ambiguity.

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 validating a price, but provides no guidance on when not to use it or alternatives. For example, if only a decision event needs to be written without checking, the sibling 'write_decision_event' would be more appropriate, but this is not 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 should disclose behavioral traits. It states the tool is a write operation (creates a hold) but does not mention permissions, rate limits, side effects, what happens on expiration, or if the hold can be removed. The behavior is minimally described.

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 with no unnecessary words. It is concise but could benefit from a brief summary of input fields. Structure is adequate for the length.

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 7 parameters, all optional, no output schema, and no annotations, the description is too brief. It does not clarify what a soft hold is relative to other holds, the duration, or what the response contains. Completeness is insufficient.

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 0%, meaning no parameter descriptions in the schema. The description does not explain any of the 7 parameters (date, agentId, players, courseId, startTime, teeTimeId, golferName). It adds no semantic value beyond their names.

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 temporary hold on a tee time before confirmation and marks the slot as soft_hold. The verb 'creates' and resource 'soft hold' are specific, and the tool is distinct from sibling tools which deal with course context, inventory, booking actions, and feedback.

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. There is no mention of prerequisites, when not to use it, or how it relates to sibling tools like check_booking_action or check_pricing_action.

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

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

No annotations are provided, so the description carries full burden. It states the tool 'explains' a result, implying no side effects, but does not explicitly confirm read-only behavior or disclose any other behavioral traits like required permissions 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 sentence that front-loads the verb and resource, providing clear purpose and audience details without extraneous information. Every word is 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?

The tool has 3 parameters including a nested object and an enum, but the description only covers the audience aspect. It lacks explanation for 'actionType' and 'result', which are required. No output schema exists, so the description should compensate but does not.

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

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

With 0% schema description coverage, the description only adds meaning for the 'audience' parameter by explaining each enum value. It does not explain the 'actionType' or 'result' parameters, which are required and lack additional context in the schema.

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

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

The description clearly states the tool explains a decision result for specific audiences, using a verb 'explains' and resource 'decision result'. However, it does not explicitly differentiate from sibling tools like 'check_booking_action' or 'write_decision_event', which might also involve explanations.

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 describing audience types (golfer, operator, developer), but it does not provide when-to-use or when-not-to-use guidelines relative to siblings. No exclusions or alternatives 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?

Discloses a key behavior: never returns protected/booked/blocked inventory. However, with no annotations provided, it fails to mention auth requirements, rate limits, or behavior when no inventory matches (e.g., empty result set).

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 focused sentences with no redundant information. Purpose is stated first, followed by a critical behavioral constraint. Every sentence 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?

For a 5-parameter tool with no output schema and no annotations, the description is severely incomplete. It omits return values, error handling, pagination, and parameter details, leaving the agent to guess or fail.

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

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

Schema has 5 parameters with 0% description coverage (no descriptions in schema). The description only vaguely references 'preferred time', failing to explain each parameter's purpose, constraints, or expected values. The agent receives no guidance on how to use parameters.

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

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

Description clearly states it finds available tee times near a preferred time and explicitly mentions it never returns non-bookable inventory. This differentiates it from sibling tools like check_booking_action or create_soft_hold.

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?

Implied usage for finding available tee times, but no explicit when-to-use, when-not-to-use, or comparison to alternatives like get_course_context. Missing guidance on prerequisites or if inventory availability may be delayed.

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 full burden. It discloses what data is returned but omits behavioral traits such as side effects, authentication requirements, or performance characteristics. A read operation is implied but not confirmed.

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: the first lists the comprehensive return data, the second provides critical usage guidance. Every word adds value; no superfluous 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 lack of output schema and annotations, the description fairly covers what the tool returns and when to use it. The list of data types is informative, though the exact return structure remains unspecified.

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 0%, and the description adds no detail about the 'date' or 'courseId' parameters beyond their names. Defaults are given, but format, constraints, or valid values are not explained.

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

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

Description clearly states it returns 'full operating context' for a course, listing specific data categories (tee-sheet, inventory, policies, etc.). This distinguishes it from siblings like get_available_inventory or check_booking_action, which are more narrow.

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?

Explicitly advises 'An agent should call this before acting,' establishing strong usage context. While it does not enumerate when not to use or provide alternatives, this directive is sufficient given the sibling tools that are more specific.

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 must disclose behavioral traits. It does not mention that the operation is read-only, safe, or any potential costs, side effects, or authentication needs. The filtering behavior is described, but that is a parameter feature, not a behavioral trait.

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 function and filtering option. No extraneous words, though it could be slightly more structured (e.g., bullet list of returned items).

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 and simple parameter list, the description adequately outlines the tool's purpose and main parameter. However, it lacks details on return format, pagination, error states, or examples, leaving some gaps for an agent to fully understand behavior.

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

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

The input schema has 0% description coverage (only types and a default). The description adds meaning for 'fingerprintKey' by clarifying it filters the results, but 'courseId' is left unexplained (only noted with default 'demo'). This partially compensates for the schema deficiency.

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 'Returns what SCP has learned' and lists concrete examples (lessons, preferences, pricing and pace patterns), making the tool's purpose specific and understandable. However, it does not explicitly distinguish the tool from siblings like get_course_context or explain_action.

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 siblings or under what conditions (e.g., prerequisites, limitations). The description only states optional filtering, leaving the agent to infer appropriate usage.

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 all behavioral traits. It mentions updating learning memory but omits side effects such as whether it is destructive, requires special permissions, or alters existing data. The word 'attaches' implies a write operation, but no further detail is given.

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 long with no wasted words, but the first sentence 'The learning tool.' is somewhat generic and could be more informative. Overall, it is efficiently 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?

For a tool with 4 parameters (including nested objects and an enum), no output schema, and no annotations, the description is severely incomplete. It does not explain the purpose of parameters, expected behavior, or return value, leaving the agent without sufficient context to 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?

Schema description coverage is 0% and the description does not explain any of the 4 parameters (decisionEventId, feedbackType, notes, metrics). It mentions 'outcome' vaguely but fails to link to the enum values or nested object structure.

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

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

The description clearly states the tool attaches an outcome to a past decision and updates learning memory, which is specific and distinct from sibling tools like write_decision_event (which likely records the decision itself). However, it does not explicitly differentiate from other feedback-related tools.

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

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

No guidance is provided on when to use this tool versus alternatives like get_learning_insights or check_* actions. The description simply states what it does without context for appropriate invocation.

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

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

With no annotations provided, the description must disclose behavioral traits. It only states that logging occurs, without mentioning side effects, permissions, reversibility, or ledger specifics. The term 'decision event' is undefined, leaving significant behavioral gaps.

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

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

The description is two sentences and front-loaded with the purpose. It is efficient but very sparse; it could include parameter hints without sacrificing 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?

With 11 parameters, no output schema, and no annotations, the description is inadequate. The agent lacks understanding of what constitutes a decision event, how to fill in required fields (e.g., toolName, actionType), and the overall ledger context. Sibling tools like 'check_booking_action' suggest a domain, but the description doesn't tie them together.

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 0%, yet the description adds nothing about any of the 11 parameters (e.g., agentId, allowed, reasons). Without parameter explanations, an agent cannot correctly populate fields beyond what the schema names imply.

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 logs a decision event to the ledger. It differentiates itself by noting that most decision tools write their own events, positioning this tool for direct logging, which provides specific verb+resource and sibling distinction.

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

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

The description explicitly states when to use: for agents that want to log an action directly, and implies that if other decision tools handle logging, this tool is unnecessary. It gives clear context but lacks explicit when-not-to-use or alternative tool names.

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