Moltline Dropship Economics

Returns Impact

returns_impact

Read-onlyIdempotent

Show what a return rate does to a margin that looked fine. PREMIUM (license).

A 10% return rate does not cost 10% of profit. A returned order gives back the refund, adds inbound shipping, and recovers only the goods — never the advertising that found the buyer. Typical input {"sell_price": 39.99, "unit_profit": 13.23, "unit_cost": 12.4, "return_rate_pct": 8, "restock_pct": 70, "return_shipping": 6} returns {"cost_per_return": 37.31, "effective_profit": 10.25, "profit_lost_pct": 22.56, "break_even_return_rate_pct": 35.46}.

Use when a category's returns are high enough to argue about. Not for the pre-returns margin itself — that is margin_check. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema

Name	Required	Description
`unit_cost`	Yes	What the goods themselves cost you — the only part a restocked unit gives back. Advertising and fees do not return.
`refund_pct`	No	Percentage of the sale price refunded, e.g. 100 for a full refund or 80 when a restocking fee is kept. Default 100.
`sell_price`	Yes	Price the customer paid.
`restock_pct`	No	Percentage of returned units resellable at full price. Default 0, the conservative case.
`unit_profit`	Yes	Profit on one kept sale, from margin_check. May be negative, which the result will make obvious.
`return_rate_pct`	Yes	Percentage of orders returned, e.g. 8.
`return_shipping`	No	What an inbound return costs you. Default 0.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.3/5.0

Behavior5/5

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

The description discloses error handling ('never raises a protocol error — it returns an error object') and idempotency/read-only nature ('Every call is read-only and idempotent'), which align with the annotations. This adds useful behavioral context beyond the annotations themselves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is somewhat verbose and includes extraneous content like 'PREMIUM (license)' and repetitive phrasing. While it is structured (purpose, example, usage, errors), it could be more concise and focused.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 parameters, output schema present), the description provides a typical input/output example, usage guidance, and error behavior. The schema covers parameter details, so the description sufficiently rounds out the context without being exhaustive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already covers parameter descriptions (100% coverage), so the baseline is 3. The description adds a concrete example with values and output, illustrating how parameters interact, which enhances understanding beyond the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool calculates the impact of return rates on profit margins, with an example input/output. It also distinguishes itself from the sibling tool 'margin_check' by indicating it is not for pre-returns margin. However, the phrasing is somewhat poetic and includes irrelevant 'PREMIUM (license)' text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly gives when to use: 'Use when a category's returns are high enough to argue about' and when not to use: 'Not for the pre-returns margin itself — that is margin_check.' This provides clear decision guidance relative to sibling tools.

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

All Moltline Dropship Economics tools Inspect

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TDQS

A4.5/5.0

Disambiguation5/5

Each tool targets a distinct economic decision: lead_time for delivery dates, margin_check for single-sale profitability, moq_planner for order quantity, price_ladder for price setting, returns_impact for return rate effects, and sku_map_check for SKU mapping validation. Cross-references explicitly point out which tool to use for adjacent concerns, eliminating ambiguity.

Naming Consistency4/5

All tool names follow a consistent noun-based pattern (lead_time, margin_check, moq_planner, price_ladder, returns_impact, sku_map_check) with descriptive suffixes. The naming is uniform and predictable, though the pattern is noun_verb rather than verb_noun, which is a minor deviation from the most common convention.

Tool Count5/5

Six tools is well-scoped for a dropship economics server. Each tool covers a distinct aspect of the domain (delivery, margin, ordering, pricing, returns, SKU mapping) without redundancy or bloat. The count is appropriate for the stated purpose.

Completeness4/5

The tool set covers the core economic decisions in dropshipping: delivery promises, margin analysis, order quantity planning, price laddering, returns impact, and SKU mapping validation. Minor gaps exist (e.g., no tool for supplier comparison or multi-product portfolio analysis), but the surface is largely complete for the stated domain.

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