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Crawlora-org

Crawlora MCP

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upwork_freelancer

Retrieve a normalized Upwork freelancer profile with verification, hourly rate, rating, reviews, and client feedback to evaluate credibility and fit.

Instructions

Get Upwork freelancer profile. Returns a normalized Upwork freelancer profile: name, title, verification badge, overview, hourly rate, rating and review count, Job Success Score, location and local time, total jobs/hours worked, and recent client feedback (title, comment, date, client name, rating). Public data sourced from Upwork's own server-rendered profile pages via a real browser-rendering backend.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesUpwork freelancer id, the value after \
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates a read operation via 'Returns' and adds valuable context about data normalization, sourcing from Upwork's server-rendered pages, and the use of a real browser-rendering backend. However, it does not mention potential failure modes, latency, or what happens for invalid IDs.

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?

The description is two focused sentences: the first states the action and resource, the second enumerates return fields and data source. Every sentence earns its place, with no filler or redundancy, and the key information is front-loaded.

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?

For a one-parameter read-only tool with no output schema and no annotations, the description is quite complete. It explains the return content in detail and the data provenance. The only notable gap is usage guidance, but it still provides sufficient context for correct invocation.

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?

The input schema provides a description for the single 'id' parameter ('Upwork freelancer id, the value after...'), achieving 100% schema coverage. The tool description does not add further detail about the parameter, but with only one parameter and high schema coverage, the baseline of 3 is appropriate.

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 opens with a specific verb+resource ('Get Upwork freelancer profile') and enumerates the exact fields returned (name, title, rating, Job Success Score, etc.). This clearly distinguishes it from sibling tools like upwork_job and upwork_search, which focus on jobs and search respectively.

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 explicit guidance on when to use this tool versus alternatives like upwork_search. The description does not state prerequisites, when not to use it, or how it relates to other Upwork tools, leaving the AI to infer usage from the tool name alone.

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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