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

Annotations already declare readOnly/openWorld, but the description adds that it is 'Free — reads stored data', discloses the return shape (evidence, impact_clicks, kind, trend, score) absent an output schema, and warns that a 0 source means the signal was never collected. It does not explain the internally inconsistent destructiveHint=true annotation, but it does not contradict readOnly either.

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 purpose and keeps every clause informational, but the single dense paragraph with nested parentheticals and caps-emphasis is heavy; splitting the signal list from the workflow guidance would read faster. Still, no sentence is filler.

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 no-output-schema, 4-param read tool this covers the essentials: what it returns conceptually, the kind/trend/score semantics, why trending items matter, the free/read nature, and dependency remediation. Grouping rules for 'several signals agree' are gestured at but the exact scoring mechanics remain implicit.

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, but the description adds real meaning: it explains what the `trends` flag actually computes (live 28-day vs prior-28-day GSC windows for rising/new demand) and what limit/detail feed ('present the top few'). That is more than the schema's terse one-liners provide.

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+resource ('Rank what this site should write or improve next') and enumerates the exact signals it consolidates (GSC page-2/low-CTR queries, rising demand, content gaps, clusters without a ranking page, tracked keywords, AI-answer prompts). It distinguishes itself from siblings by naming the tools that feed it rather than produce the same output.

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?

Positions the tool explicitly in a workflow ('Start of the content_engine workflow: present the top few to the user and let them choose') and gives a presentation rule ('Lead with trending ones when presenting'). It also explains how to remediate empty signals by pointing at sync_search_console, compute_content_gaps, create_keyword_session, add_tracked_keywords and run_visibility_scan, though it never names a sibling to use *instead* when this tool is the wrong choice.

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