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run_poshmark_items_likes

Fetch users who liked a Poshmark listing by ID or URL, returning each liker's handle, name, and avatar for audience research.

Instructions

Users who liked a Poshmark listing (handle, name, avatar), by listing id or URL. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemYesListing. e.g. Listing id or URL, e.g. 6865651dd6c0dc3f3fdfc8ea
domainNoDomain. Options: poshmark.com = poshmark.com, poshmark.ca = poshmark.ca
max_itemsNoMax likes (up to 500)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.1

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden, but it does add two useful behavioral facts: the shape of the returned records (handle, name, avatar) and the cost model ('1 point per returned record'). It omits auth requirements, pagination/cursor behavior, and whether max_items truncates silently, which matters for a paid, capped scrape.

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?

Two short sentences with no padding, and the resource/return shape is front-loaded before the cost note. Could be tighter still, but nothing is wasted.

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

Completeness3/5

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

With no output schema and no annotations, the description is the only source of behavior, and it covers just identity-of-resource, return fields, and per-record cost. It leaves out response envelope, pagination, and error/permission conditions, which is thin for a billed endpoint, though the schema handles the inputs fully.

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 all three parameters (item, domain, max_items) are already documented in the schema, including that item accepts an id or URL. The description's 'by listing id or URL' merely restates the schema, adding no new semantics; baseline 3 applies.

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?

States a specific resource and relationship: users who liked a given Poshmark listing, plus the fields returned (handle, name, avatar). The name and description together make it distinguishable from run_poshmark_items_comments or run_poshmark_users_followers without opening a schema, though it never names or contrasts a sibling explicitly.

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

Usage Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives such as run_poshmark_users_followers (user-level following) versus this listing-level likes endpoint. The agent must infer usage entirely from the name.

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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