Scan one live Polymarket negRisk event for fee-adjusted outcome-sum violations. Intelligence only; verify CLOB depth and resolution rules before acting.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Polymarket event slug | |
| min_edge | No | Minimum net edge, default 0.02 | |
| min_liquidity | No | Minimum liquidity per leg in USD, default 1000 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite empty annotations, description clarifies it is non-destructive and intelligence-focused. Warns about verification steps, offering behavioral context beyond the annotation defaults.
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?
Two concise sentences front-load the main action. Every word is purposeful, zero waste.
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?
Adequately describes purpose, usage constraints, and parameter context. Lacks output format details, but for a scanning tool this is acceptable given no output schema.
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 coverage is 100%, so baseline is 3. Description adds no additional parameter-level meaning beyond the schema's comments. It provides overall context but does not enhance individual parameter understanding.
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 explicitly states specific verb 'Scan', resource 'live Polymarket negRisk event', and targeted analysis 'fee-adjusted outcome-sum violations'. It clearly distinguishes from siblings like 'polymarket_market_scan'.
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?
Explicitly states 'Intelligence only' (read-only, not actionable) and instructs to 'verify CLOB depth and resolution rules before acting', providing clear when-not and necessary follow-up.
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.
Tools cover very diverse domains (weather, FDA, legal, crypto, etc.), so cross-domain confusion is low. However, within domains there is notable overlap: multiple food recall tools (food_recall_check, food_safety), multiple weather tools (weather_current_global, weather_forecast_grid, weather_alerts, weather_bias), and several Polymarket-related tools. This can cause agent misselection.
Naming is inconsistent: some tools use verb_noun (search_arxiv, scrape, validate_agent_manifest), others use noun phrases (smart_money, space_weather, tide_data), and some are long descriptive phrases (cross_platform_arb_scan, polymarket_event_scan). No single pattern is followed, making predictions difficult.
95 tools is excessively high for any coherent purpose. The server appears to be a random aggregation of APIs with no clear scope. Such a large catalog overwhelms agents and dilutes utility; most tools could be split into specialized servers.
Although many domains are touched, each is covered only shallowly. For example, weather lacks historical data, legal lacks case details beyond court opinions, and financial lacks stock prices. There are obvious gaps like no user authentication or data persistence. The tool set feels like a collection of endpoints rather than a cohesive service.