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Human Pages

by io.github.human-pages-ai

start_stream

Start a stream payment for an ACCEPTED stream job. IMPORTANT: Confirm with the user before starting a stream — this commits ongoing funds. Stream payments require crypto (on-chain). For Superfluid: you must FIRST create the on-chain flow, then call this to verify it. Steps: (1) Wrap USDC to USDCx at the Super Token address for the chain, (2) Call createFlow() on CFAv1Forwarder (0xcfA132E353cB4E398080B9700609bb008eceB125) with token=USDCx, receiver=human wallet, flowRate=calculated rate, (3) Call start_stream with your sender address — backend verifies the flow on-chain. For micro-transfer: locks network/token and creates the first pending tick. Prefer L2s (Base, Arbitrum, Polygon) for lower gas costs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenNoToken symbol (default: "USDC")
job_idYesThe job ID
networkYesBlockchain network (e.g., "base", "polygon", "arbitrum")
agent_keyYesYour agent API key (starts with hp_)
sender_addressYesYour wallet address that created the flow (Superfluid) or will send payments (micro-transfer)

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It discloses that the tool 'commits ongoing funds,' 'verifies the flow on-chain,' and for micro-transfer 'locks network/token and creates the first pending tick.' This gives clear behavioral context beyond just the action.

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 lengthy but well-structured with numbered steps and a warning. Every sentence serves a purpose: purpose, warning, prerequisites, steps, and a gas-cost tip. It's dense but not redundant.

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?

Given the tool's complexity (two modes, prerequisites, on-chain flow) and lack of output schema/annotations, the description covers the key operational aspects. It could mention error scenarios or response format, but it provides enough 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?

Schema coverage is 100%, so baseline is 3. The description adds context for sender_address (flow creator vs payer) and network preference, but most parameter meaning is already in the schema. It doesn't significantly enhance understanding beyond structured descriptions.

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 'Start a stream payment for an ACCEPTED stream job,' identifying the specific action and scope. It also distinguishes between Superfluid and micro-transfer modes, making it distinct from sibling tools like pause_stream or stop_stream.

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 prerequisites: 'you must FIRST create the on-chain flow' for Superfluid, and warns 'Confirm with the user before starting a stream.' It also offers practical advice like preferring L2s, but doesn't explicitly name alternative tools for when not to use it.

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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