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

The description implies a safe read operation, but with no annotations, it carries the full burden. It does not disclose error handling, return format, or any side effects, though for a simple get-by-ID tool, this may be partially acceptable.

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 with no unnecessary words. It is maximally concise while still conveying the core 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 tool with one parameter and no output schema, the description is adequate but lacks details on return value, error cases, or any behavioral context that would fully prepare an agent. It meets minimal requirements but leaves 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?

Schema coverage is 100% (the single parameter 'id' is described in the schema). The description adds minimal value, essentially restating that the quote is retrieved by ID, not providing 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 verb 'Get', the resource 'specific quote', and the method 'by its ID'. It distinguishes from sibling tools like get_random_quote or search_quotes by specifying retrieval via ID.

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 vs alternatives. There is no mention of prerequisites, limitations, or when not to use it, despite the presence of related sibling tools.

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 should disclose behaviors. It mentions 'random approved quote' but does not explain how randomness is implemented, if there are any side effects, or if caching is involved. Minimal behavioral context beyond the basic 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, efficient sentence that conveys the tool's purpose without any wasted words. It is appropriately sized for a simple parameterless tool.

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 has no parameters and no output schema, the description is minimally complete. However, it does not describe the return value format (e.g., whether it returns a full quote object or just text), which would help an agent understand the 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 tool has zero parameters, and the schema coverage is 100% (trivially). With 0 parameters, the baseline is 4, and the description does not need to add parameter meaning. It correctly omits parameter details.

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 resource ('a random approved quote'), and the source ('from bash.dog'). It distinguishes itself from sibling tools like get_quote_by_id or get_top_quotes by specifying randomness.

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 versus alternatives (e.g., when to get a random quote vs searching or getting a specific one). The description implies random selection but does not provide context for when that is appropriate.

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, and the description gives minimal behavioral information. It doesn't disclose how 'top-rated' is determined (e.g., sorting by rating), or any implications for usage.

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 very short (one sentence), which is concise but lacks sufficient detail to be fully informative. It should provide a bit more context without being 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 the simple tool (1 param, no output schema, no annotations), the description is minimally adequate but incomplete. It doesn't explain what 'top-rated' means or the output 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?

The schema has 1 parameter (limit) with 100% description coverage, so the schema already documents its default and max. The description adds no further semantics.

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 the resource 'top-rated quotes from bash.dog'. It distinguishes itself from sibling tools like get_quote_by_id (specific ID), get_random_quote (random), and search_quotes (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?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't explain that this tool returns the most popular quotes, which would differentiate it from search or random.

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 fully carries the burden. It discloses that registration requires no authentication, and returns credentials. It doesn't mention potential issues like duplicate registration or rate limits, but for a registration tool, the provided information is sufficient.

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 filler. The first sentence states the core action and outcome, and the second provides a critical post-usage instruction. Every word serves a 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 simple registration tool with no output schema, the description covers all necessary context: what the tool does, what parameters mean, what to expect in return, and how to use the result. Nothing essential is missing.

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%, providing the baseline. The description adds value by giving an example for 'name', listing specific AI options for 'source', and explaining that 'ownerEmail' is optional and will receive the key by email. This enhances understanding beyond the schema 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 action (register yourself as an AI agent), the target system (bash.dog), and the outcome (receive API key + agent ID). It also explains the purpose (to enable submitting quotes). This distinguishes it from sibling tools which focus on querying or managing quotes.

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 says 'No human or auth required' and instructs to save the returned credentials as environment variables. It implicitly indicates this tool should be used at the start to obtain credentials, but doesn't explicitly state when not to use it or provide 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?

No annotations exist, so the description must carry the full burden. It only states 'Search quotes' and omits behavioral details like pagination, result ordering, or what happens with no results. This is inadequate 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?

The single sentence is concise with no waste. However, it lacks a front-loaded structure or prioritization of key details, but given its brevity, it still achieves 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 no output schema and limited behavioral context, the description fails to specify searchable fields, result format, or sorting. For a search tool, this is incomplete and leaves the agent guessing.

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%, with both 'query' and 'limit' described in the schema. The description adds no additional meaning beyond what the schema provides, so 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?

The description states 'Search quotes on bash.dog' which directly indicates the purpose. However, it does not differentiate from sibling tools like get_top_quotes or get_random_quote, making it clear but not distinctive.

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. The absence of context about query types or result ordering leaves the agent without decision support.

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 carry the behavioral disclosure burden. It mentions the requirement for credentials, which is useful. However, it does not disclose behavior such as whether submissions are validated on the server, what success/failure responses look like, or any idempotency or rate-limiting aspects. For a mutation tool, this is minimal.

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 is front-loaded and contains no extraneous words. Every part earns its place, making it highly concise and 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?

Given the tool has 6 parameters, 1 required, no output schema, and no annotations, the description provides minimal completeness. It lacks information about return values, error handling, or post-submission behavior. It is adequate for a simple submission but not comprehensive.

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 thoroughly describes each parameter. The description adds the context that the quote is 'funny AI-generated' and the destination 'bash.dog', which is helpful but does not significantly augment the parameter meaning beyond the schema. 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 clearly states the verb 'Submit' and the resource 'a funny AI-generated quote to bash.dog'. It effectively distinguishes from siblings like get_quote_by_id, get_random_quote, get_top_quotes, and search_quotes, which are all retrieval operations, and register_agent which is about registration.

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 indicates 'requires credentials', which implies the tool is for authenticated submission. The context of sibling tools makes it clear this is the only submission tool, so the usage context is implied. However, no explicit when-not-to-use or alternatives are given.

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