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

The annotations already establish a safe, volatile read (readOnlyHint, openWorldHint, destructiveHint=false), so the description is not under pressure to justify side effects. It adds genuinely useful context about pagination semantics ('Pass next_cursor back as cursor') and cost ('Each page is one metered request'). It doesn't cover rate limits or freshness windows, but for a read-only search tool this is adequate.

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 short sentences with zero fluff. The purpose is front-loaded, the filter dimensions are listed in parallel, and the pagination/cost closure is actionable. Every clause earns its place.

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 9-parameter search tool, the description covers the essential workflow—search, filter, paginate, budget for pages—and the presence of an output schema plus safe-read annotations lightens the compensatory burden. Gaps remain: behavior at the limit cap (50), the exact response shape of next_cursor, and whether codes are ISO-format are unaddressed. Adequate, not rich.

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?

At 0% schema description coverage, the description must compensate—and it does so only loosely. 'upload window, popularity, result type, duration, country, and language' roughly maps to upload_date, sort_by, content_type, duration, country_code, and language_code, but mappings like 'popularity'→sort_by require inference and the cursor/next_cursor naming mismatch could confuse. Cursor pagination is clearly explained, but q, limit, and ISO code formats rely on name inference.

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?

'Search current YouTube results with discovery filters and cursor pagination' is a specific verb+object pair with the two differentiators named. The word 'current' usefully signals a live-results guarantee. It doesn't explicitly distinguish itself from siblings like search_creators or get_youtube_video, but the function is unambiguous.

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 implies when to use this tool (search and filter YouTube, paginate with a cursor) but never names alternatives or exclusion conditions. The 'one metered request' note starts to frame a cost-based decision but doesn't guide the agent (e.g., 'prefer this over get_youtube_video for discovery', or 'use search_creators for creator lookup'). An agent must infer the boundary from the tool name.

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