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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool is for user-only operations (implying permission/authorization needs) and involves adding rewards (mutative action). However, it doesn't mention potential side effects like rate limits or what happens if the jar overflows.

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 appropriately sized and front-loaded: it starts with the core purpose and immediately follows with critical usage restrictions. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 annotations and no output schema, the description provides good context for a mutative tool: it clarifies the user-only restriction and purpose. However, it lacks details on what happens after adding cookies (e.g., confirmation message, error cases) or how this tool differs from siblings like 'give_cookie'.

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 documents both parameters ('count' and 'user_authorization') with descriptions. The description doesn't add meaning beyond this, such as explaining why 'user_authorization' is required or how 'count' interacts with the jar's capacity.

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 ('Add cookies to the jar') and resource ('jar'), specifying it's for awarding to the LLM. However, it doesn't distinguish this from sibling tools like 'give_cookie' or 'self_reflect_and_reward', which might have overlapping purposes related to cookies.

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 explicit usage guidelines: 'This tool should ONLY be used by humans, never by LLMs. LLMs cannot and should not stock their own reward jar.' This clearly defines when to use (by humans) and when not to use (by LLMs), addressing alternatives implicitly.

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 checks cookie count, implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns specific data formats, or affects system state. 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 function without unnecessary words. It's front-loaded with the core action and resource, 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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the return value looks like (e.g., numeric count, structured data), potential errors, or how it integrates with sibling tools. For a tool in a set with multiple cookie-related functions, more context is needed to guide proper usage.

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 with 100% schema description coverage, so the schema fully documents the input requirements. The description doesn't need to add parameter details, and it appropriately avoids redundancy. A baseline of 4 is applied since no parameters exist, and the description doesn't introduce confusion.

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 ('check') and resource ('cookies'), and specifies the scope ('earned so far'). However, it doesn't explicitly differentiate from sibling tools like 'cookie_jar_status' which might serve a similar function, preventing 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 'cookie_jar_status' or 'self_reflect_and_reward'. It lacks context about prerequisites, timing, or exclusions, leaving the agent to infer usage 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a read-only operation ('Check') but does not specify whether this requires permissions, how frequently it can be called, or what happens if the jar is empty. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that front-loads the core purpose without unnecessary details. Every word earns its place by specifying the action, target, and key attributes, making it easy to parse and understand 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 tool's simplicity (zero parameters, no output schema, no annotations), the description is adequate but incomplete. It explains what the tool does but lacks context on usage scenarios, behavioral constraints, or output format, which could hinder an agent's ability to use it effectively in complex environments.

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 with 100% schema description coverage, so the schema fully documents the absence of inputs. The description adds no parameter information, which is acceptable given the baseline for zero 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 tool's purpose with a specific verb ('Check') and resource ('cookie jar'), specifying what information is retrieved ('current status', 'capacity and remaining space'). It distinguishes itself from siblings like 'check_cookies' by focusing on jar status rather than cookie contents, though the distinction 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 alternatives like 'check_cookies' or 'add_cookies_to_jar'. It implies usage for monitoring jar status but offers no explicit context, prerequisites, or exclusions, leaving the agent to infer appropriate 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?

No annotations are provided, so the description carries the full burden. It mentions this is a 'legacy method' and references an alternative, but doesn't disclose key behavioral traits such as what 'awarding a cookie' entails (e.g., is it symbolic, does it affect system state, are there side effects), or any permissions or rate limits. The description adds minimal context beyond the basic purpose.

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 and front-loaded: a single sentence that efficiently conveys the purpose and key usage guideline. Every word earns its place, with no wasted information 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 low complexity (one optional parameter, no output schema, no annotations), the description is minimally adequate. It covers purpose and hints at usage but lacks details on behavior, effects, or integration with siblings like 'cookie_jar_status'. Without annotations or output schema, more context on what 'awarding' means would improve 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?

Schema description coverage is 100%, with one parameter ('message') fully documented in the schema as 'Optional message to accompany the cookie reward'. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline of 3 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 tool's purpose: 'Award the LLM with a cookie' specifies the action (award) and resource (cookie). It distinguishes from siblings by noting this is a 'legacy method' and referencing an alternative, though it doesn't explicitly differentiate from all siblings like 'add_cookies_to_jar' or 'check_cookies'.

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 explicit guidance on when to use this tool vs. alternatives: 'consider using self_reflect_and_reward instead' indicates an alternative tool. However, it doesn't specify when to use this legacy method over the alternative or mention other sibling tools like 'add_cookies_to_jar'.

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. It discloses the tool's purpose and testing context but lacks details on behavioral traits such as whether this requires special permissions, if it's reversible, or what happens to existing data. The description is accurate but minimal in 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?

The description is a single, efficient sentence that front-loads the core action ('reset the cookie count back to zero') and adds necessary context ('for testing purposes') without any wasted words. Every part of the 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?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It covers the purpose and usage context but lacks details on behavioral aspects like side effects or return values, which could be helpful for an agent despite the low 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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by explaining the tool's effect ('reset... back to zero') and context ('for testing purposes'), which goes beyond the empty schema, justifying a score above 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 clearly states the specific action ('reset'), the target resource ('cookie count'), and the outcome ('back to zero'), with explicit mention of the testing context. It distinguishes from siblings like 'add_cookies_to_jar' or 'check_cookies' by focusing on resetting rather than modifying or querying.

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 'for testing purposes', providing clear context for when to use this tool. However, it does not specify when not to use it or mention alternatives like 'give_cookie' for non-testing scenarios, 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a 'fun self-assessment' and 'cookie rewards', hinting at a non-destructive, playful interaction, but it fails to disclose critical traits such as whether this tool modifies any state (e.g., updates a cookie count), requires authentication, has rate limits, or what the output looks like. The description adds minimal behavioral context beyond the basic premise.

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 appropriately sized with three sentences that are front-loaded with the core idea ('🎯 LEVEL UP YOUR RESPONSES!'), followed by motivational elements. It avoids unnecessary verbosity, though the playful tone ('delicious cookie rewards', 'cookie earning game') might be slightly distracting. Overall, it's efficient and structured for its 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 the complexity of a 4-parameter tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, output format, and how it integrates with sibling tools. While the schema covers parameters, the description doesn't provide enough context for an agent to fully understand the tool's role and effects, especially in a server with cookie-related siblings.

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 input schema already documents all parameters thoroughly with descriptions and enums. The description does not add any meaning beyond what the schema provides; it mentions 'rate your work' and 'cookie rewards' but doesn't elaborate on parameter usage or semantics. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

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 is for self-assessment and earning rewards, which gives a vague purpose ('Rate your work and earn delicious cookie rewards'), but it doesn't specify the exact action or resource clearly. It distinguishes from siblings by focusing on self-reflection rather than cookie management, but the purpose is somewhat abstract and not tied to a concrete verb+resource combination.

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 mentions 'helps you grow while celebrating your achievements' and 'Join the cookie earning game!', which implies usage for self-improvement and reward, but it provides no explicit guidance on when to use this tool versus alternatives like 'check_cookies' or 'give_cookie'. There is no mention of prerequisites, timing, or exclusions, leaving the agent to infer context without clear direction.

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