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List gigs in a category

list_gigs

Scrape live Fiverr search results for a query to return gig cards with seller, rating, reviews, price, and URL, helping you scout competitor offerings and pricing.

Instructions

Scrape live Fiverr search results for a query and return gig cards with title, seller, rating, review count, entry price and URL. Use this to scout what sellers are actually offering and charging.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
max_priceNo
min_priceNo
min_ratingNo
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

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 burden alone. It usefully discloses that results are scraped live (implying fresh, network-dependent, non-deterministic data) and what each card contains, but says nothing about rate limits, rate-limit/blocking risk, auth needs, or pagination behavior for a 5-parameter 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 tight sentences with the operation front-loaded and the returned fields listed compactly. No filler, though it spends words on return contents that the output schema already covers.

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?

An output schema exists, so return-value explanation is not strictly needed, and the call signature is simple. But with 0% parameter documentation and no annotations, the definition leaves an agent guessing about filter semantics and scrape behavior (limits, failures) it must handle.

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

Parameters2/5

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

Schema description coverage is 0% across 5 parameters, so the description must compensate and it does not. It never explains the query syntax, the units/scope of max_price and min_price (entry price?), min_rating's scale, or what max_results does when more matches exist.

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 verb+resource ('Scrape live Fiverr search results ... return gig cards') and enumerates the returned fields, so the operation is unambiguous. It does not differentiate itself from siblings like price_gig or analyse_market, whose scopes could plausibly overlap with 'scouting what sellers are charging'.

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?

'Use this to scout what sellers are actually offering and charging' hints at intent (market reconnaissance) but gives no when-to-use boundaries, no prerequisites, and no guidance on when to prefer price_gig or analyse_market over this search-based listing.

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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