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

With no annotations, the description carries the burden and does well: it discloses the default state filter, sort order, paging mechanism, and the full set of returned summary fields plus the 'meta' escape hatch. Auth requirements and rate limits are unaddressed, but core behavior is transparent.

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?

Three dense sentences, all front-loaded with the scope, default behavior, and result shape. No filler; every clause conveys operational information.

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?

Despite having no output schema, the description enumerates the returned fields and explains filtering defaults and pagination, giving the agent everything needed to call and interpret the result 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?

Schema coverage is 100%, so baseline is 3, but the description adds cross-parameter semantics the schema does not: the finished-only default, the meta field-expansion pattern, and start/count paging. This is meaningful added meaning beyond per-field 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?

States a specific verb plus resource ('List Scrapy Cloud jobs of a project') and adds scope details (newest first, per-project). This cleanly distinguishes it from singular siblings like scrapy_cloud_get_job and filtered variants.

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?

Explains a crucial default ('Returns only finished jobs unless state is given') and how to page ('Use start with count'). It stops short of naming sibling alternatives, but the when-to-use context is clear.

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