Draft new posts modelled on a top post

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

Annotations only establish the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=false, idempotentHint=false). The description goes well beyond them by disclosing that nothing is published or scheduled, that the call consumes the account's daily AI quota, and that availability is plan-gated – exactly the quota and side-effect context an agent needs before invoking.

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?

A single dense paragraph that is well front-loaded: what it writes and what it reuses comes first, constraints and return shape last. There is minor redundancy – the post_id provenance is stated in both the description and the schema, and the sentence chain is long – but no sentence is wasted.

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?

With no output schema, the description compensates by inlining the return shape ({ drafts: { <platform>: { text, title?, tags? } }, reference }). Combined with the quota, plan-gating and no-publish disclosures, an agent has everything needed to call this tool correctly and interpret the result.

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 description coverage is 100%, so post_id, topic, platforms and brand_voice are already documented, including the platform default. The description largely restates the schema (published-post ids from performance results, new topic vs new angle) without adding format or interaction detail, so the schema-baseline of 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?

The description names a specific verb and resource ('Writes new drafts, one per platform') and pins down the mechanism precisely: reuse of structure, opening type, length, format and tone from a reference post, with an explicit negative ('the reference post's sentences are not reused'). It is distinguishable from generate_posts in substance, but it never names that sibling, so the differentiation is left for the agent to infer.

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?

It states clear operating context: the required id must come from the account's post performance results, nothing is published or scheduled, it counts toward the daily AI limit, and availability depends on the plan. What is missing is explicit routing against alternatives such as generate_posts or plan_week, so the when-to-use-this-instead signal is absent.

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