create_rejections_in

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

The description goes well beyond the minimal annotation set by disclosing operational caveats: godown behavior, extrapolated XML shape, the LINEERROR date-period failure and its set_period workaround, and voucher-numbering edge cases. It also honestly flags uncertainty about the exact voucher format.

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 longer than average, but every sentence carries operational value: purpose, scope, caveats, and troubleshooting. It is front-loaded with the core definition and then adds necessary behavioral detail.

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 complex write tool with no output schema and sparse annotations, the description covers the key risks an agent needs to know: required godowns, active-period date failures, auto-numbering pitfalls, and the need to verify results. It is sufficiently complete for reliable invocation and error recovery.

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 coverage is 100%, so the schema already documents the parameters well. The description adds useful context around godown auto-filling and voucherNumber retry behavior, but most parameter semantics are already present in the input 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 clearly states the specific action: creating a Rejections In voucher in TallyPrime. It explains the business scenario (goods rejected and returned by a customer or job worker) and distinguishes it from sales/purchase vouchers by noting it is inventory-movement-only with no party ledger.

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 gives clear context on when to use this tool: when goods are being returned to the company as rejected. It does not explicitly name alternatives like create_rejections_out, but the scenario is specific enough for an agent to select it appropriately.

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