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wasintoh

line-oa-mcp-ultimate

by wasintoh

Get LINE coupon redemption stats

line_get_coupon_stats
Read-onlyIdempotent

Get coupon stats by combining raw coupon details and optional click audience data to estimate redemptions. Includes notes on data source limitations.

Instructions

Read available stats for a LINE coupon. We combine multiple signals because LINE's Coupon API does not (yet) expose a dedicated redemption-events endpoint:

  1. Raw coupon detail (LINE GET /v2/bot/coupon/{id}) — some accounts include usage fields inline.

  2. Click-audience size (if you pass click_audience_id) — proxies "users who clicked through".

Args:

  • coupon_id: ID of the coupon (from line_manage_coupon mode='list' or mode='create').

  • click_audience_id: optional numeric audience id to enrich the report.

  • oa: optional OA id.

  • response_format: 'markdown' (default) | 'json'.

Returns (structured): { coupon_id, raw: {...whatever LINE returned about the coupon...}, click_audience?: { id, name, audience_count, status }, estimated_redemptions?: number, notes: string[] // explains data sources clearly }

Notes:

  • For an accurate redemption count, build your coupon Flex with a postback action and listen for postback events via a webhook server (V2 webhook-server companion).

  • Click audience size approximates "clickthroughs", not actual redemptions — surface this caveat to the user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
coupon_idYes
click_audience_idNoOptional — if you created a click audience from the coupon broadcast, pass its id to enrich the stats with click-through count.
oaNo
response_formatNomarkdown
Behavior4/5

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

Annotations already indicate readOnly and non-destructive. The description adds value by explaining how it combines data sources, returns structured output, and highlights caveats (e.g., click audience approximates clickthroughs, not redemptions). It lacks mention of potential rate limits or authentication requirements.

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

Conciseness4/5

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

The description is well-structured with sections (signals, Args, Returns, Notes) and front-loads purpose. However, it includes detailed implementation specifics (LINE API endpoints) that could be streamlined for brevity.

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

Completeness5/5

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

Despite no output schema, the description provides a detailed Returns structure and Notes with important caveats. It covers functionality, parameters, output format, and limitations, making it complete for the tool's complexity.

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?

Schema coverage is low (25%), but the description compensates by explaining each parameter's purpose (e.g., coupon_id from line_manage_coupon, click_audience_id to enrich stats, oa optional, response_format default markdown). It adds meaning beyond the schema.

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

Purpose5/5

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

The description clearly states it reads stats for a LINE coupon, combining multiple signals. It distinguishes itself from the sibling tool line_manage_coupon (create/list) by focusing on stats retrieval.

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

Usage Guidelines3/5

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

The description implies usage for reading coupon stats but does not explicitly state when to use or not use, nor does it mention alternatives beyond the note about webhook for accurate counts. The alternative is hinted but not framed as a clear when-to-use guideline.

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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