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

No annotations are provided, so the description carries the full burden, and it does real work: it declares read-only behavior, the single-workspace scope, and the important null-vs-0 semantic for ad_spend_cents ('null means we cannot answer, 0 would assert nothing was spent'). It stops short of describing pagination, latency, or auth requirements beyond the token param, so it is strong but not exhaustive.

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-loaded with purpose, then usage, then the null-vs-0 caveat that materially changes interpretation. The three sentences are dense but each earns its place; only the null caveat sentence runs slightly long.

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 read-only analytics tool with no output schema, the description covers intent, scope, returned data shape, and the one ambiguous output value (ad_spend_cents null vs 0). An agent has everything needed to call it 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 description coverage is 100%, so the schema already documents window_days, workspace_id, and autowhisper_token, including the omission-defaults-to-current-workspace rule. The description adds no parameter-level syntax or format detail beyond the 'ONE workspace' scoping emphasis, 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 — read-only cross-channel performance for ONE workspace — and enumerates the returned structures (four-layer funnel, per-channel breakdown, ad spend). It explicitly distinguishes itself from autowhisper_feed and autowhisper_posts, which 'only say what was made and sent, never whether it worked.'

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 explicit when-to-use ('answer how published content is actually doing, and before advising which creative to fund or scale') and names the sibling tools it supersedes for that question. Nothing about tool selection is left to inference.

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