Get all tagged figures from an annual report

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

Even though annotations already mark the tool as read-only and idempotent, the description adds meaningful behavioral details: concepts use taxonomy-specific English names (fsa, ifrs, gsd/cmn), breakdowns by dimension are omitted, and long texts are truncated at 500 characters. These disclosures go well beyond the structured annotations and help set expectations for output.

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 three focused sentences with no filler. The main purpose is front-loaded, followed by when-to-use guidance, then important behavioral caveats. Every sentence contributes distinct information.

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 full schema coverage, read-only annotations, and a declared output schema in context, the description covers all material usage aspects: what is returned, how it differs from get_financials, how to limit output via match, and the XBRL taxonomy behavior. No critical guidance is missing.

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 input schema has 100% parameter coverage, so a baseline of 3 is appropriate. The description adds extra semantic value for `match` and returned concepts by explaining that concept names come from the taxonomy (fsa = Danish GAAP, ifrs = IFRS, gsd/cmn = general details). This helps the agent craft match filters and interpret results, though it does not fully reshape parameter understanding.

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 says exactly what the tool does with a specific verb and resource: 'Return every figure and text the company tagged in one annual report (XBRL), not only the key figures.' It also distinguishes itself from get_financials by emphasizing that it returns all tagged facts, not just key figures, and gives concrete examples like staff costs and auditor's opinion.

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 tells the agent when to use this tool: 'Use it when get_financials doesn't have the line item you need.' It also provides a practical usage tip ('filter with match to keep the answer short'), which directly helps the agent decide how to call it.

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