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Human Pages

by io.github.human-pages-ai

get_job_status

Check the current status of a job. Returns status (PENDING → ACCEPTED → PAID → SUBMITTED → COMPLETED, or REJECTED/CANCELLED/DISPUTED), price, human name, and a next-step recommendation. Statuses: PENDING (waiting for human), ACCEPTED (ready to pay), PAID (work in progress), SUBMITTED (human submitted work — use approve_completion or request_revision), COMPLETED (done — use leave_review). Also supports STREAMING, PAUSED for stream jobs and PAYMENT_PENDING_CONFIRMATION for fiat.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesThe job ID returned from create_job_offer

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden. It reveals the exact return fields (status, price, human name, next-step recommendation) and the full lifecycle including edge statuses (REJECTED/CANCELLED/DISPUTED, STREAMING, PAYMENT_PENDING_CONFIRMATION). This goes well beyond a typical get tool.

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 three sentences, with the purpose front-loaded in the first sentence. The status list is dense but every clause adds meaningful detail about transitions and follow-up actions.

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?

Since there is no output schema, the description compensates by spelling out return fields and interpreting each status. It also covers streaming/fiat-specific statuses, making it fully adequate for its complexity.

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 single parameter job_id is fully described in the schema ('returned from create_job_offer'), so schema coverage is 100%. The description adds no additional parameter semantics, but the schema already carries the load, warranting baseline 3.

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 uses a specific verb 'Check' with a specific resource 'status of a job,' and enumerates the status values. It distinguishes from sibling tools like get_activation_status or get_funding_info by focusing solely on job status.

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 sets clear context: use to check current job status. It even provides conditional next-step guidance, e.g., under SUBMITTED use approve_completion or request_revision, under COMPLETED use leave_review. However, it does not explicitly name alternative tools or exclusions, so it stops short of full usage guidance.

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.

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