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

Annotations already establish read-only and idempotent behavior, so the bar is lower. The description goes further by disclosing status lifecycle, 24h TTL for job_id, and a summary of the completed report contents (risk_tier, compliance checklist, ISO 42001 alignment, etc.). This adds meaningful operational context beyond the annotations.

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 a single dense sentence but every clause conveys useful information—statuses, TTL, report fields, timing. It is front-loaded with the action ('Poll the result') and avoids filler words. While it could be split into two sentences, it is efficient and well-structured.

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 polling tool, the description covers the full lifecycle: when to call, what each status means, what happens on expiry, and the key output fields. Since an output schema exists, it doesn't need to fully document return types, but the description provides a strong overview of the expected result. The inclusion of deadlines and recommendation priorities shows thorough coverage.

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?

The schema description for job_id already includes the prefix (aigfr_) and origin from ai_governance_full_report_async, so coverage is 100%. The tool description adds no additional parameter-level semantics beyond what the schema provides, but that is not required given the high coverage. 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?

The description uses the specific verb 'Poll' and clearly identifies the resource as the result of ai_governance_full_report_async. It explicitly names the sibling async tool, distinguishing it from other result tools like competitive_deep_dive_result. This is a clear, non-tautological statement of purpose.

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 explicitly instructs the agent to call this after the eta_seconds hint returned by ai_governance_full_report_async (~90s). It also explains when each status (pending, completed, failed, not_found) appears, giving the agent criteria to decide whether to keep polling or abandon. This is strong usage guidance with a specific timing recommendation.

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