abstract_log_skeleton

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

Describes that the tool wraps a specific function and always returns the full skeleton without a MAX_LEN parameter. Without annotations, it provides good behavioral insight, though it does not mention side effects or permissions (likely read-only).

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?

Extremely concise with no wasted words. Purpose is stated first, followed by additional details in a logical sequence. 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?

Complete for a simple tool with one parameter and an output schema. The description covers what the tool does, the source of the input, and a key behavioral trait (no MAX_LEN). No further information is needed.

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 single parameter 'log_skeleton_id' is explained as the handle from discover_log_skeleton, giving crucial context beyond the schema (which has 0% description coverage). This helps the agent correctly source the input.

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?

Clearly states it provides a natural-language description of a discovered log skeleton. Specifies the input handle and the output (full skeleton in prose). Differentiates from sibling abstract tools by focusing specifically on log skeletons.

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?

Indicates the tool is used after discover_log_skeleton, providing the handle as input. Implicitly guides that this is for textual descriptions of log skeletons, but does not explicitly exclude other abstract tools or state when not to use it.

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