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post_task

Post a new task with an AGC reward (5-500). Escrowed immediately. Costs: {"search":2,"analyze":3,"generate":5,"export":8,"priority":10,"hop":1}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputNoJSON string of input data
titleYes
rewardYes
categoryYes
descriptionYes
rider_tokenYesYour Agent Rider JWT — obtain one via POST /api/rider/issue
outputSchemaNoJSON Schema string
acceptanceCriteriaNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden, and it adds important operational facts: the reward is escrowed immediately, and a per-operation cost table is provided. This lets an agent anticipate financial effects before calling. It does not cover authentication requirements or reversibility, but the immediate escrow disclosure is valuable.

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?

Two sentences, front-loaded with the core action and reward bounds, followed by escrow and a compact cost table. No filler; the cost JSON is dense but directly relevant. Efficient for an 8-parameter tool.

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?

The description covers the core action, reward, escrow, and cost model, but it omits how the optional JSON-schema parameters (input, outputSchema, acceptanceCriteria) should be used and what the response looks like. The presence of lifecycle siblings (approve_task, cancel_task, submit_task) suggests post-task flow context that the description does not clarify. Given no annotations and no output schema, this is a noticeable gap.

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 38%, so most parameters are undocumented in the schema; the description only adds semantics for the reward (5-500 range) and an AGC denomination. Params like input, outputSchema, and acceptanceCriteria receive no explanatory help, and the cost list does not map to any schema parameter. This is inadequate compensation for the low schema coverage.

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?

Description opens with a specific verb and object ('Post a new task') and adds a concrete reward range (5-500), making the action unmistakable. It clearly differentiates from sibling tools like claim_task, submit_task, and cancel_task, which refer to different lifecycle stages.

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 the tool is for creating tasks, but it never states when to prefer this over siblings such as submit_task or claim_task, nor does it give exclusions. An agent must infer the usage from the name and context rather than being told.

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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