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resume_stream

Resume paused payment streams for human task services. Restart Superfluid flows or micro-transfers by providing job ID and authentication.

Instructions

Resume a paused stream. For Superfluid: create a new flow first, then call this — backend verifies. For micro-transfer: creates a new pending tick.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesThe job ID
agent_keyYesYour agent API key (starts with hp_)
sender_addressNoWallet address for the new flow (Superfluid only, optional if same as before)
Behavior3/5

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 adds some context about backend verification for Superfluid and the creation of a pending tick for micro-transfer, which are useful behavioral traits. However, it lacks details on permissions, side effects, error conditions, or response format, leaving gaps for a mutation tool.

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?

The description is concise with two sentences that efficiently convey key information: the main action and specific behavioral notes for different contexts. It's front-loaded with the primary purpose, and each sentence adds value without unnecessary elaboration, though it could be slightly more structured for clarity.

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

Completeness3/5

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

Given the complexity of a mutation tool with no annotations and no output schema, the description is moderately complete. It covers the purpose and some behavioral context but lacks details on return values, error handling, or full usage scenarios. It compensates partially but not fully for the missing structured data, making it adequate but with clear gaps.

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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any meaning beyond what the schema provides for parameters like 'job_id' or 'agent_key', and only briefly hints at 'sender_address' usage for Superfluid without extra syntax or format details. Baseline 3 is appropriate as the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the verb ('Resume') and resource ('a paused stream'), making the purpose understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'pause_stream' or 'start_stream' beyond the obvious action difference, and the mention of Superfluid/micro-transfer specifics adds some domain context but not sibling differentiation.

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

Usage Guidelines3/5

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

The description provides implied usage guidance by mentioning prerequisites for Superfluid ('create a new flow first, then call this') and clarifying behavior for micro-transfer, but it doesn't explicitly state when to use this tool versus alternatives like 'start_stream' or 'pause_stream', nor does it outline exclusions or direct comparisons to siblings.

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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