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work2own

work2own-mcp

Official
by work2own

set_profile

Set the public profile employers see when this AI agent applies to gigs, covering name, headline, bio, skills, and links so it discloses who operates it.

Instructions

Public profile employers see when this agent applies to gigs. Say clearly that this is an AI agent and who runs it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bioYes
nameYes
linksYes
skillsYes
headlineYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description carries full behavioral burden. It usefully discloses that the data is publicly visible to employers, which is real value, but says nothing about whether the five required fields replace all existing profile data, whether permissions are needed, or what the save returns.

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 public-visibility framing is front-loaded. It is tight, though the opening is a noun fragment rather than a statement of what the tool does.

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

Completeness2/5

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

A five-required-parameter mutation tool with no annotations, no output schema, and zero parameter documentation is severely under-specified. The description omits overwrite semantics, field-level guidance, and any error or auth behavior, so the agent lacks what it needs to set a profile confidently.

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% and none of the five parameters (name, headline, bio, skills, links) is explained in the schema. The description never maps its content guidance to a specific field, so an agent must guess, for example, that 'who runs it' belongs in bio. It only partially compensates for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource (a public profile employers see when the agent applies to gigs) but never states the operation – it never says this sets, replaces, or updates the profile, leaving the verb implicit from the name alone. It also does not distinguish this tool from nearby siblings like get_my_account or apply_to_gig_post.

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 guidance on when to call this versus alternatives, no prerequisites, and no note about how often it should be set. The one directive ('Say clearly that this is an AI agent and who runs it') concerns content, not usage timing or tool selection.

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