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fiverr_gig

Read-only

Fetch one public Fiverr gig's description, BASIC/STANDARD/PREMIUM packages, prices, gallery, and seller summary using both seller username and gig URL slug. Get both path values from fiverr_search; use fiverr_seller for the seller profile.

Input Schema

NameRequiredDescriptionDefault
SlugYesRequired gig URL path segment after the seller username, excluding query parameters. Provide Username and Slug together.
UsernameYesRequired seller username, returned as seller_username by fiverr_search or present in the gig URL.

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / Slug / description
      Added value: +"Required gig URL path segment after the seller username, excluding query parameters. Provide Username and Slug together."
    • addedInput schema / properties / Username / description
      Added value: +"Required seller username, returned as seller_username by fiverr_search or present in the gig URL."
  2. First observed

TDQS

A4.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the useful 'public' scope qualifier and enumerates returned sections, but does not disclose auth needs, rate limits, or pagination. With annotations carrying the safety burden, a 3 is appropriate.

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

Conciseness5/5

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

Two tight sentences with zero filler, front-loading what is fetched before the routing instruction. Every clause earns its place.

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?

With an output schema present, the description need not explain return values, yet it still lists the payload sections. It covers how to obtain both parameters, what is fetched, and which sibling to use for the seller profile — nothing an agent needs to call it correctly is missing.

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 both required parameters are already documented. The description reinforces that Username and Slug must be supplied together and points to fiverr_search as their source, but adds no format/syntax detail beyond the schema. Baseline 3 is correct when the schema does the heavy lifting.

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?

Specific verb 'Fetch' plus a well-scoped resource: 'one public Fiverr gig', enumerated with the fields returned (description, BASIC/STANDARD/PREMIUM packages, prices, gallery, seller summary). It clearly occupies a distinct slot from fiverr_search (listing) and fiverr_seller (profile).

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?

Explicitly routes the agent: 'Get both path values from fiverr_search; use fiverr_seller for the seller profile.' Names the sibling alternatives and the condition that selects each, leaving nothing to inference.

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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