tally_get_voucher

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

With no annotations provided, the description carries the full burden and does so excellently. It discloses duplicate-voucher behavior (returns all matches), default period logic (Indian financial year), period echoing, timeout risks, prompt-injection warning about text fields, and the read-only nature of the server. This goes far beyond basic operation.

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 structured with clear section headers (WHEN TO USE, RETURNS, AMBIGUITY, PERIOD) and every sentence provides actionable information. It is longer than average but each part earns its place, covering purpose, usage, edge cases, security, and constraints without redundancy.

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?

Despite lacking an output schema, the description covers return content (voucher with ledger entries), ambiguity handling, date defaults, timeout behavior, and safety warnings. For a single-record fetch tool, this is complete and leaves no critical operational questions unanswered.

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?

Although schema coverage is 100%, the description adds substantial semantic value: it explains the default range behavior when both dates are omitted, clarifies that includeAllFields defaults to true and why, describes the company mismatch error behavior, and ties date range to performance. This meaningfully supplements the raw schema.

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 states the exact operation: 'Fetch a single voucher by its voucher number within a period.' This clearly distinguishes it from sibling tools like tally_list_vouchers (listing) and tally_search_vouchers (searching) by focusing on retrieving a known voucher in full.

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?

Explicit WHEN TO USE guidance is provided: 'to inspect one transaction in full once its number is known, typically from tally_list_vouchers or tally_search_vouchers.' It also gives specific usage rules: supply both dates or neither, and warns about timeouts for long ranges, which helps the agent decide when to use this tool.

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