update_stock_journal

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

Beyond the annotations (readOnlyHint=false, destructiveHint=true), the description discloses real behavioral risk: 'Tally's Alter lookup ignores voucher type and can silently corrupt the wrong one' and that the tool 'Refuses if another voucher type shares the same number on that date.' This is exactly the kind of non-obvious, high-stakes behavior an agent needs to know before invoking a destructive update.

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 dense sentences with no filler. The primary action is front-loaded, followed by the key distinction from create_stock_journal, then the critical look-up precondition and failure mode. Every sentence earns its place and the most important safety information comes at the end without being buried.

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?

The description covers the matching strategy, required preconditions, and a dangerous collision scenario, which is substantial for a complex update tool. However, since there is no output schema, a brief note about what the tool returns (e.g., success confirmation or updated voucher details) would make it fully complete. Minor gap only.

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 description coverage is 100%, so the baseline is 3. The description adds value by explaining the composite matching key: 'Matched by date + voucher number,' which gives semantic meaning to date and voucherNumber beyond their individual schema descriptions. It also reinforces that voucherType must match the original type for the lookup to succeed, which is useful parameter relationship guidance.

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 opens with a specific verb and resource: 'Update an existing Stock Journal voucher in TallyPrime', and specifies the exact scope: 'replacing its source/destination lines and narration.' It also differentiates from the likely sibling create_stock_journal by stating 'Same fields as create_stock_journal, plus voucherNumber,' so an agent can immediately distinguish update from create.

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 gives explicit preconditions: 'use get_ledger_vouchers or get_vouchers first to confirm it exists and is unique.' It also tells the agent what to do on collision: 'resolve the collision in Tally first.' It does not explicitly state when-not-to-use this tool or name alternative update tools like update_voucher, but the context is clear enough for correct routing.

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