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FLUF-io

@fluf/mcp

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by FLUF-io

list_drafts

Retrieve a seller's unsent listing drafts, including failed marketplace submissions that need fixes and pending-review items awaiting approval.

Instructions

List the seller's review drafts: listings FLUF has prepared but not sent. A failed draft is one a marketplace refused for a reason the seller can fix — the reason says what it objected to, and fields holds every value with editable: true on the ones that can be changed (a select field lists its options). A pending_review draft is simply waiting for a go-ahead. Read a draft, decide the corrected value from the product itself (never invent one), then call approve_draft with the edits. Once the item is live on that marketplace its draft leaves this list on its own.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-indexed page. Default 1.
searchNoMatch on the product title.
statusNo'failed' = a marketplace refused the listing for something an edit fixes (size, brand, category, price, wording); 'pending_review' = the seller asked to review that marketplace before anything goes live; 'open' (default) = both.
channelNoOnly drafts for this marketplace (e.g. 'ebay', 'vinted'). Omit for all; the response's `by_channel` says where the drafts are.
per_pageNoResults per page. Default 50, max 100.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.7

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it explains that `failed` means a marketplace refused for a fixable reason, that `reason` holds the objection and `fields` carries editable values, that `pending_review` is merely awaiting go-ahead, and that drafts disappear from the list once the item goes live. It stops short of stating pagination behavior or any permission/auth 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?

Front-loaded with the core purpose, then layers state semantics and the next action in four tight sentences. Dense but every clause carries information; no filler or repetition of the tool name.

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?

There is no output schema, so the description usefully documents the meaningful return shape (reason, fields, editable flags, select options) as well as the lifecycle behavior. Missing only minor items such as pagination echo or sorting, which is acceptable for a filtered-list tool.

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

Parameters3/5

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

Schema description coverage is 100%, so every parameter is already documented in the schema, including the status enum meanings and by_channel note. The description adds workflow meaning around statuses but no syntax or format detail beyond what the schema supplies, so baseline 3 applies.

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?

Opens with a specific verb+resource ('List the seller's review drafts') and immediately scopes it as 'listings FLUF has prepared but not sent', which separates it from sibling list_products and from approve_draft. The definition of each draft state makes the object of the tool unambiguous.

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

Usage Guidelines4/5

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

Explicitly routes the agent onward: read the draft, derive the corrected value from the product itself ('never invent one'), then call approve_draft with the edits. That is clear when-to-use context and names the next tool. It does not, however, contrast with alternatives like list_products or discuss when not to call it.

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