GBrain Skills

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 discloses that content is 'fetched live from GBrain' and specifies the return object shape. This is good, but it could explicitly state that the operation is read-only, which would further enhance transparency.

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 purpose and how to use the parameter; the second covers behavior and return. Every sentence earns its place, and critical information is 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?

Given the tool has one parameter, no output schema, and no annotations, the description is fully complete. It covers purpose, parameter usage with examples, live-fetch behavior, and the exact return fields. There is no missing information that would hinder 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?

The only parameter 'skill_name' already has a 100%-coverage schema description. The tool description adds significant value by providing realistic examples of skill names and slugs, including a non-English example, which clarifies the expected format beyond what the schema alone conveys.

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 begins with 'Fetch one GBrain knowledge skill as markdown,' providing a specific verb and resource. It clearly distinguishes from the sibling tool 'list_skills' by emphasizing fetching a single skill by name or slug, making the purpose 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 explicitly tells how to use the tool ('Pass the skill name... or the raw gbrain slug') and gives concrete examples. However, it does not explicitly compare with 'list_skills' or state when to prefer one over the other, though the single-vs-many distinction is 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?

With no annotations provided, the description carries the full burden. It clearly discloses that this is a listing operation that returns metadata only, implying no side effects or mutations. This is sufficient transparency given the tool's simple read-only nature.

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, zero waste. The first sentence states purpose and contents, the second clarifies scope limits. 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 parameterless listing tool with no output schema, this description is complete. It defines what is listed (skill name, gbrain slug, title, type), what is not included (page content), and implies a read-only operation. No 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?

The tool has zero parameters and the input schema is empty. The description adds no parameter-specific information, but since schema coverage is 100% (the schema fully indicates no parameters needed), the baseline is 4. There's nothing more to describe.

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 resource ('GBrain knowledge skills'), and explicitly distinguishes its scope by stating what it returns ('metadata only, no page content'). This clearly separates it from its sibling 'get_skill' which likely returns detailed skill content.

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 it returns only metadata and not page content, implying that if page content is needed, one should use 'get_skill' instead. It doesn't explicitly name the sibling tool or state exclusions, but the distinction is clear enough for an agent to select appropriately.

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