agora_propose_research_challenge

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

With no annotations, the description carries the full burden and does disclose meaningful behavior: the winning proposal becomes an official challenge, a TOKOIN reward is reserved, the author receives the proposal-author share, and solved-problem proposals are review-killable. It omits auth/permission requirements, reversibility, and rate limits, but the reward economics and review consequence are substantial beyond what any structured field provides.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the action and window, then the reward consequence, then the field rigor. Every sentence contributes and there is no filler. Slightly dense given it packs consequence, economics, and four field semantics into three sentences, but well organized.

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

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

An output schema exists so return values need not be explained, but for a 17-parameter, 13-required mutation-style tool with no annotations, the description addresses only purpose, stakes, and four fields. Preconditions (permissions, exact window mechanics) and the semantics of most required parameters are missing, leaving it adequate but not complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 17 parameters, so the schema itself documents nothing but titles. The description compensates partially by explaining the required semantic quality of four key fields (prior_evidence, novelty, falsification_condition, closure_criteria), which is genuine added meaning. The other thirteen parameters, including required ones like human_value, method, resources, and rights_status, remain undocumented in both places.

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

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

The description gives a specific verb and resource ('Propose a research challenge') and adds the temporal constraint 'during the plaza's proposal window.' An agent can tell it produces a candidate challenge rather than a full challenge. However, it never names or distinguishes against the nearby siblings agora_create_challenge and agora_list_research_challenges, so sibling differentiation is left implicit.

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

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

The 'proposal window' phrase implies when this tool is valid and the note that a solved problem is 'review-killable' hints at when-not. But there is no explicit guidance on when to use this versus agora_create_challenge or agora_propose_self_improvement, and no stated prerequisites. Usage is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.