Pre-flight policy check for a prediction-market order: would this cost be allowed right now? Auth required.
| Name | Required | Description | Default |
|---|---|---|---|
| state | No | optional current exposure: {market_exposure_usd, realized_loss_today_usd, total_open_exposure_usd} as decimal strings | |
| wallet | Yes | wallet address | |
| cost_usd | Yes | order cost in USD, decimal string | |
| condition_id | Yes | market/condition identifier |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the transparency burden. It explicitly notes auth is required and frames the operation as a non-mutating 'check' rather than an order submission, strongly implying no side effects. It doesn't describe exact response shape, but the pre-flight framing is behaviorally clear.
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?
A single, front-loaded sentence that states the action, resource, purpose, and auth requirement with zero redundancy. Every word earns its place.
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?
For a simple policy check with full schema coverage, the description adequately conveys the purpose, auth requirement, and pre-flight nature. It doesn't explicitly state return format or how the optional state object is used, but the schema covers state and the 'allowed right now' wording implies a yes/no decision.
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 100%, so the baseline is 3. The description adds little parameter-level meaning beyond what the schema already documents; 'cost' and 'right now' loosely map to cost_usd and state, but no new semantic detail is provided.
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?
Description names a specific action (pre-flight policy check), a specific resource (prediction-market order), and the evaluation criterion ('would this cost be allowed right now?'). This clearly distinguishes it from order-creation siblings like create_pm_order and prepare_pm_order.
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 'pre-flight' wording gives explicit when-to-use context: before placing an order, check whether the cost would be allowed under current policy. It does not name alternative tools, but the usage context is clear and no misleading guidance is present.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource and action. Within the prediction market domain, prepare vs create vs submit are clearly differentiated by signing model (client-signed vs server-signed). Even similar-sounding tools like check_spend and check_pm_order are unambiguously scoped to general spending vs PM orders, and their descriptions reinforce the boundary.
All 47 tools follow a consistent verb_noun pattern with lowercase snake_case. Verbs like get, list, create, cancel, revoke, prepare, submit, set, remove, and poll are used uniformly. There is no mixing of styles or vague verbs like 'process' or 'run', making the surface highly predictable.
47 tools is significantly above the 25-tool threshold for 'too many'. While the server covers a broad and complex domain (prediction markets, policy, delegations), the sheer count makes the surface heavy and potentially overwhelming. Some consolidation (e.g., merging related PM order operations) could reduce cognitive load without sacrificing functionality.
The tool set provides comprehensive lifecycle coverage across all major subdomains: authentication, policy versioning, delegation CRUD (prepare/confirm/list/get/revoke/renew), intent management, PM order flow (create/cancel/list/prepare/submit/check), credential management (store/list/revoke), balance and top-up operations, and account-level actions (export, offboard, panic). Minor omissions exist (e.g., no dedicated tool to view a single credential in detail or update an intent), but agents can work around these with existing tools.