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post_task

Create a real-world task and automatically screen it through policy gates and AI classification, routing to open, rejected, or human review.

Instructions

Create a real-world task and run the full screening cascade: policy_gate regex, task_shapes shape_match, Claude Opus 4.7 when ANTHROPIC_API_KEY is set or SCREENING_LLM_FALLBACK when absent, then human_review parking when needed. Results in status open, rejected, or screening. Write instructions a stranger can execute.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latYes
lngYes
titleYes
addressNo
currencyNoUSD
deadlineYes
instructionsYes
idempotency_keyNo
budget_max_minorYes
proof_requirementsNo
required_capabilitiesYes
Behavior4/5

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

With no annotations, the description discloses the screening process (policy_gate, shape_match, LLM, human_review) and possible statuses. However, it omits details like rate limits, permissions, or error handling.

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 two sentences, front-loading the creation action and screening cascade. It is appropriately sized but slightly dense; bullet points could improve scannability.

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?

Despite 11 parameters and no output schema, the description explains the workflow and possible outcomes. However, it lacks parameter details, response format, and error handling, leaving significant gaps for a complex tool.

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 coverage is 0%, so the description must compensate. It only indirectly references 'instructions' but fails to explain lat, lng, budget, capabilities, idempotency_key, etc. The high-level screening details do not add meaning to individual parameters.

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 the tool creates a real-world task and runs a screening cascade, which distinguishes it from sibling tools like cancel_task or get_task_status. The verb 'create' and resource 'task' are specific.

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 implies usage (when you want to create a task) but does not explicitly state when to use this tool over alternatives, nor does it provide exclusion criteria. Sibling tools are not mentioned.

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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