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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), the description discloses that drafts are scored against the brand's voice, queued in 'All Content' for approval, and never auto-published. It also states the candidate limit of 25 per call. This substantially enriches the agent's understanding of what happens after invocation.

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 more expansive than the minimal ideal, but nearly every sentence earns its place: purpose, prerequisite, scoring feedback loop, platform rule, queue outcome, limit, and exclusion of community campaigns. It is front-loaded with the core purpose and keeps the most important constraints early. Slight redundancy around the queue and scoring costs a point.

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 write-oriented tool with no output schema, the description covers prerequisites, parameter constraints, side effects, approval flow, and the intended alternative. It tells the agent where results will appear (get_content_queue) and what will not happen (no auto-publishing). Nothing critical for correctly selecting and invoking the tool 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 coverage is 100%, so the baseline is 3. The description adds meaningful semantic detail beyond the schema, especially the platform constraint: 'platform must be one of the space's platforms (omit it to use the first).' It also reinforces the 25-candidate limit and the default template behavior, which helps correct 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 opens with a specific verb and resource: 'Draft one or more posts into a ProductClank content space.' It then differentiates this tool from create_content_campaign, clarifying that this writes into the user's own content pipeline rather than a community campaign. This is a clear, non-tautological purpose statement that an agent can act on.

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 gives explicit when-to-use guidance: 'Call get_content_workspace FIRST', use the space's platforms, and omit platform to use the first. It also names the alternative for community campaigns: 'use create_content_campaign for that.' The conditions are concrete and leave little to inference.

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