get_gstr1_summaryGSTR-1 outward-supply summary for a period: B2B / B2CL / B2CS section totals and the HSN-wise rollup, for return preparation.
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | Reporting period: mtd (default), last-month, qtd, or ytd. |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds behavioral context by listing what data is included (section totals and HSN rollup) and the purpose (return preparation). It does not mention data freshness or auth, but the read-only nature is well covered by 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, front-loaded sentence that packs the resource, scope, included data, and use case without wasted words. Every phrase contributes meaning.
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 a single well-documented parameter, full schema coverage, read-only annotations, and an output schema, the description provides sufficient context. It explains the tax form and its contents, making the tool's role clear. No further details about return values are needed given the output schema.
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% for the single period parameter, including an enum and default value. The description only reinforces 'for a period' without adding meaning beyond the schema, so the 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 clearly states the tool provides a GSTR-1 outward-supply summary for a period, specifying the included sections (B2B/B2CL/B2CS) and HSN-wise rollup. This distinguishes it from sibling tax tools like get_hsn_summary or get_tax_summary by naming the exact resource and scope.
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 phrase 'for return preparation' gives clear context for when this tool is appropriate. It does not explicitly exclude alternatives, but the focused scope makes the intended use obvious. A minor gap is the lack of explicit comparison to similar siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Most tools target distinct data points (e.g., get_analytics_summary vs get_brand_score). However, 'search' and 'search_catalog' have overlapping functionality and could cause confusion, and 'fetch' is a helper tied to 'search', adding minor ambiguity.
The majority use consistent verb_noun snake_case (e.g., get_inventory, list_stores). Exceptions like 'fetch' and 'search' (without object) break the pattern, but they are few.
43 tools is excessive for a data-retrieval-only API. Many get_* and search_* tools could be consolidated (e.g., search_catalog, search_inventory, search_orders are similar). The large number will overwhelm an agent.
The tool set is entirely read-only (get, search, list, fetch). There are no create, update, or delete tools, which is a critical gap for managing e-commerce operations. Agents can only view data, not act on it.