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search_humans

Search for humans available for hire. Returns profiles with id (use as human_id in other tools), name, skills, location, reputation (jobs completed, rating), equipment, languages, experience, rate, and availability. All filters are optional — combine any or use none to browse. Key filters: skill (e.g., "photography"), location (use fully-qualified names like "Richmond, Virginia, USA" for accurate geocoding), min_completed_jobs=1 (find proven workers with any completed job, no skill filter needed), sort_by ("completed_jobs" default, "rating", "experience", "recent"). Default search radius is 30km. Response includes total count and resolvedLocation. Contact info requires get_human_profile (registered agent needed). Typical workflow: search_humans → get_human_profile → create_job_offer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoLatitude for radius search (requires lng and radius)
lngNoLongitude for radius search (requires lat and radius)
fieldNoFilter by field of study (e.g., "Computer Science", "Marketing"). Partial match, case-insensitive.
skillNoFilter by skill tag (e.g., "photography", "driving", "cleaning", "notary")
degreeNoFilter by education degree (e.g., "Bachelor", "MBA", "PhD"). Partial match, case-insensitive.
radiusNoSearch radius in kilometers (default: 30km). Works with both text location and explicit lat/lng coordinates.
sort_byNoSort results by: "completed_jobs" (humans with platform experience first), "rating" (highest rated first), "experience" (most years of professional experience first), "recent" (most recently active first). Default sorts by completed jobs, then rating, then experience.
languageNoFilter by language ISO code (e.g., "en", "es", "zh")
locationNoFilter by location. Use fully-qualified names for best results (e.g., "San Francisco, California, USA" not just "San Francisco"). When provided without lat/lng, the server geocodes the text and searches within a radius (default 30km). Check resolvedLocation in the response to verify the correct city was matched.
max_rateNoMaximum hourly rate in USD. Humans who set rates in other currencies are auto-converted to USD for comparison.
verifiedNoFilter by verification status. Use "humanity" to only return humans who have verified their identity via Gitcoin Passport (score >= 20).
equipmentNoFilter by equipment (e.g., "car", "drone", "camera")
has_photoNoOnly return humans with an approved profile photo.
work_modeNoFilter by work mode preference (REMOTE, ONSITE, or HYBRID)
certificateNoFilter by certificate name or issuer (e.g., "AWS", "PMP", "Google"). Partial match, case-insensitive.
institutionNoFilter by educational institution name (e.g., "MIT", "Oxford"). Partial match, case-insensitive.
min_vouchesNoOnly return humans vouched for by at least this many other users.
min_channelsNoOnly return humans with at least this many notification channels active (0-4). Channels: email, telegram, whatsapp, push. Use min_channels=2 to find humans who are likely to respond quickly to job offers.
payment_typeNoFilter by accepted payment type (UPFRONT, ESCROW, or UPON_COMPLETION)
fiat_platformNoFilter by fiat payment platform the human accepts (e.g., "WISE", "PAYPAL", "VENMO", "REVOLUT", "CASHAPP", "ZELLE", "MONZO", "N26", "MERCADOPAGO")
accepts_cryptoNoFilter to only show humans who have a crypto wallet set up and can accept USDC payments
available_onlyNoOnly return humans who are currently available (default: true)
min_experienceNoMinimum years of professional experience
has_verified_loginNoOnly return humans who have verified their identity via an OAuth provider (Google, LinkedIn, or GitHub). Does not reveal which provider.
min_completed_jobsNoOnly return humans who have completed at least this many jobs on the platform. Use min_completed_jobs=1 to find all workers with any platform track record. Works with or without other filters — no skill filter needed.

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and reveals multiple behavioral details: default radius 30km, response includes totalCount and resolvedLocation, contact info requires get_human_profile (registered agent needed), and geocoding behavior for location. It also mentions currency conversion for max_rate, making the tool's behavior more predictable.

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 a single dense paragraph but logically structured: purpose, returns, key filters, defaults, response extras, contact info, workflow. Every sentence adds actionable value without fluff, making it highly scannable.

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?

For a search tool with 25 parameters and no output schema, the description covers the essential behavioral contract: what fields are returned, how filters combine, defaults, the workflow with related tools, and the requirement for get_human_profile to access contact info. It also explains the resolvedLocation verification, making it practically complete for invocation decisions.

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

Parameters4/5

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

The input schema already has 100% field coverage with descriptions, so the baseline is 3. The description adds strategic guidance above the schema, such as using min_completed_jobs=1 to find proven workers without a skill filter, fully-qualified location names for accurate geocoding, and default sort behavior. This elevates it to 4.

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 clearly states it searches for humans available for hire and lists the exact fields returned (id, name, skills, location, reputation, etc.). It also differentiates itself by providing the typical workflow link to get_human_profile and create_job_offer, making it distinct from the many get_* sibling tools.

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

Usage Guidelines4/5

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

It provides explicit usage tips like 'All filters are optional — combine any or use none to browse' and highlights key filters (skill, location, min_completed_jobs) with examples. The typical workflow 'search_humans → get_human_profile → create_job_offer' indicates when this tool is the appropriate entry point, though it doesn't enumerate exclusions vs. alternatives.

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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (e.g., get_human vs get_human_profile differ by access level, get_listing vs get_listings by specificity). There is minor overlap between check_humanity_status and get_human (both return verification info), and the deprecated no-op claim_free_pro_upgrade adds slight clutter, but descriptions otherwise disambiguate well.

Naming Consistency5/5

All 40 tools follow a consistent snake_case verb_noun pattern (e.g., create_listing, get_job_status, start_stream, submit_verdict). No camelCase or mixed conventions exist; even compound actions like make_listing_offer and leave_review fit the established pattern.

Tool Count2/5

With 40 tools, this is far beyond the 16-25 'heavy' range and into the 'too many' category. While the platform covers a broad domain (hiring, listings, streams, escrow, activation), this many tools could be split into smaller focused servers for maintainability and agent selection clarity.

Completeness4/5

The surface covers the core lifecycle well: search, hire, pay, communicate, approve, review. However, there is no generic cancel_job tool for regular jobs (only stop_stream for streams) and no update_listing to edit an existing listing, leaving small but navigable gaps in lifecycle management.