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

Annotations already provide readOnlyHint=true, openWorldHint=true, and idempotentHint=false, covering safety and unpredictability. The description adds the behavioral detail of 'present the first sentence first, then the reveal', which is a unique two-step presentation mechanic not inferable from annotations. However, it does not disclose other behaviors like whether the random selection is truly uniform, whether exclude is respected, or how seed affects results. Given annotation coverage, the additional context warrants a 3.

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, so it is concise in length. However, it is more poetic than informative, using 'serendipity' and 'shelf at random depth' without concrete grounding. It front-loads an evocative label rather than a functional statement. While it wastes no words, it also does not earn its place by conveying actionable information. Under-specification is closer to a 2 than a 5.

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 4 parameters, no output schema, and 0% schema coverage, the description must carry the full burden of explaining what the tool does, what it returns, and how parameters affect results. It does none of this. The metaphor of 'shelf' and 'depth' is undefined, and the reveal mechanic is not operationalized. The description is severely inadequate for an agent to call this 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?

The input schema has 4 parameters (seed, count, intent, exclude) with 0% description coverage. The description entirely ignores these parameters, providing zero hints about their purpose, defaults, or allowed values. The agent has no way to know what seed controls, what intent means, or how exclude works. This is a severe gap that the description must compensate for, and it fails to do so.

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 metaphorical language ('Serendipity spin: a random shelf at random depth — present the first sentence first, then the reveal') to convey the concept of a blind-date-with-a-book tool. It implies a random book pick with a reveal mechanic, but does not explicitly state the core function (e.g., 'returns a random book suggestion'). It distinguishes from siblings only through the serendipity/randomness angle, which is implicit rather than explicit. Not tautological, but vague enough to score a 3.

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 given on when to use this tool versus siblings like recommend or free_classics. The description does not mention alternatives, conditions, or exclusions. The 'serendipity' notion implies a use case, but it is left entirely to the agent to infer. No explicit 'use this when...' or 'avoid when...' is present.

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?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering safety and idempotency. The description adds 'readable in full right now', which communicates that content is immediately accessible without paywalls or restrictions—a useful behavioral detail. However, it does not clarify response format or how results are presented, so it adds limited value beyond the annotations.

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, tightly written sentence that immediately communicates the core value proposition. It is front-loaded with the key information (public-domain, Project Gutenberg, readable in full) and contains no filler. While it could add a bit more detail without becoming verbose, its brevity is a strength.

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 that the tool has three optional parameters and no output schema, the description is notably incomplete. It does not mention what the tool returns (e.g., a list of titles, metadata, links), how the parameters influence results, or any edge cases like limits or error behavior. An agent has insufficient information to call this tool effectively, especially as the schema lacks parameter descriptions.

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 fails to explain any of the three parameters (count, topic, intent). Since the schema provides no descriptions, the tool description is the only source of parameter meaning, but it remains silent. Agents must guess what 'count' (number of results?), 'topic' (subject filter?), and 'intent' (user's goal?) mean, which is nearly impossible without external knowledge. The description does not compensate at all for the schema gap.

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: providing public-domain classics from Project Gutenberg, readable in full. It specifies a distinct resource and action, making the tool's function understandable. However, it does not differentiate from sibling tools like 'recommend' or 'blind_date' that might also involve books, so it doesn't fully distinguish itself.

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 the listed siblings. There is no mention of preferred contexts, alternative tool suggestions, or exclusions. The tool's optional parameters (count, topic, intent) hint at filtering, but no explicit usage conditions are stated, leaving the agent to infer.

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?

Annotations already declare readOnlyHint=true, openWorldHint=true, and idempotentHint=true, covering safety and determinism. The description adds context about the scale ('millions of works') and the presence of free-read flags, which is useful supplemental information. However, it does not disclose any other behavioral traits such as result ordering, pagination, or handling of ambiguous topics. This is a modest addition beyond annotations.

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, concise sentence that front-loads the core purpose ('Book recommendations') and elaborates on input modes. Every phrase adds value and there is no redundancy or fluff. Excellent structural efficiency.

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 4 parameters, 0% schema coverage, and no output schema, the description is under-sized. It provides a high-level gist but omits critical details like parameter mapping, expected output format, handling of missing or ambiguous inputs, and any constraints or defaults (e.g., count default). An agent would need to guess parameter meanings and result structure, making the description insufficiently complete for correct 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?

Schema description coverage is 0%, so the description must compensate by explaining parameters. It mentions 'topic, mood, or books like X', which hints that 'topic' maps to the topic parameter, 'mood' might map to intent, and 'books like X' could involve topic and exclude, but no explicit mapping is given. The description fails to clarify the meaning of 'count', 'intent', or 'exclude' adequately, leaving the agent to infer parameter usage from the schema's bare names. This is insufficient for seamless invocation.

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 a specific verb ('recommend') and resource ('books') and lists three input modes (topic, mood, 'books like X'). It does not explicitly distinguish itself from sibling tools like blind_date or free_classics, though the mention of 'free-read flags' hints at one differentiator. Overall purpose is clear but sibling differentiation is absent.

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 when to use the tool (when recommendations based on topic/mood/similarity are needed) but offers no explicit guidance on when not to use it or how it compares to alternatives. No exclusions or alternative tool mentions are provided, so the usage context is only implied.

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?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, so the safety and repeatability profile is known. The description adds minimal behavioral context beyond purpose—it says 'full content' (return size) and references the source of the name. It does not contradict annotations and adds small value without redundancy.

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 with no filler. The core action is front-loaded ('Fetch the full content of one skill'), followed by the key constraint ('by name') and the source. 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?

This is a simple, read-only tool with one parameter and no output schema. The description tells the agent what it returns ('full content') and where the name comes from. Combined with annotations, the agent has everything needed to call it correctly. 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 description coverage is 0%, so the description must compensate. It does by specifying that the 'name' parameter is the skill name taken from skills_list. This adds meaning beyond the bare schema property, telling the agent how to obtain a valid value. It does not define format, but the source is sufficient for a single string parameter.

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 a specific verb ('Fetch'), a resource ('full content of one skill'), and the key parameter ('by name'). It also references the source of the name ('from skills_list'), which distinguishes it from sibling tools like skills_list that list all skills. This is unambiguous.

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 context: you need a skill name, and that name comes from skills_list. It does not explicitly name alternatives or when-not-to-use, but the reference to skills_list gives clear guidance on where names originate. This provides enough context without being explicit about exclusions.

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?

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds meaningful context by defining what skills are (guidance playbooks) and their purpose (using the server well). It does not contradict annotations and provides useful domain context beyond the structured fields.

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?

A single sentence that front-loads the core action ('List available skills'), immediately defines the resource, and ends with an actionable pointer to the sibling tool. Every word earns its place; there is no fluff.

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, parameterless, read-only listing tool, the description is complete. It tells the agent what the tool returns (a list of skills), what those skills are, and how to proceed (skill_read). No output schema exists, but the simplicity makes that acceptable. The annotations cover safety, so nothing 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?

The tool has zero parameters, so there is nothing to document. Per the rubric, a baseline of 4 applies for 0 params. The description adds no parameter information because none exists, and the schema correctly shows an empty properties object.

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') and a resource ('available skills'), clarifies they are 'guidance playbooks', and directly distinguishes from the sibling tool skill_read by pointing to it as the next step. This is a precise, unambiguous purpose statement.

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 tells the agent when to use this tool (to see the list of skills) and when to use the alternative skill_read ('read one with skill_read'), providing clear routing between the two related tools. This matches the standard of the get_calls example.

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