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

Goes well beyond the annotations: it discloses that every fetch records a download/acquisition (explaining why readOnlyHint=false and idempotentHint=false), that repeated calls create new receipts, and that content can change after updates. It also specifies auth requirements (free needs no login; paid needs X-API-Key or Bearer token plus prior purchase), states that no purchase is made, describes the return shape, and warns that content may be a source link rather than embedded text.

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?

Front-loads the core purpose, then layers usage, side effects, and auth in scannable paragraphs, ending with an example. Each sentence carries information, though the auth/purchase passage is dense enough that it could be tightened.

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 one-parameter tool with full schema coverage and an output schema, nothing an agent needs to call it correctly is missing: purpose, sibling routing, side effects, auth prerequisites, and the application_id handoff to report_outcome are all present.

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% and the schema already documents the single slug parameter, including what it is not ('not a URL or asset ID'). The description only adds a concrete sample call, which is helpful but adds little semantic meaning beyond the structured field, so the baseline 3 applies.

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?

States a specific verb and resource — retrieving the raw content (prompt text, skill instructions, agent config) of a Spark asset — and explicitly distinguishes the payload ('the actual text to apply, not just a description of it'). It also contrasts with the sibling get_asset, so an agent can tell the two apart without opening either schema.

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?

Gives the selection condition directly ('For when a known asset's content is needed for application') and names the alternative with its differing behavior ('get_asset provides details without acquisition'). This is exactly the when-to-use-this-vs-sibling guidance an agent needs.

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