get_markets_near_resolutionPolymarket markets resolving within the next N hours with a leading probability above threshold. Useful for resolution arbitrage and last-minute positioning.
| Name | Required | Description | Default |
|---|---|---|---|
| hours | No | Maximum hours until resolution (default: 24h, max: 168h = 7 days) | |
| min_prob | No | Minimum leading outcome probability to include (default: 0.7 = 70%) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint. The description adds behavioral context (returns markets resolving soon with leading probability) but does not describe additional traits like pagination or rate limits. No contradiction with annotations.
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 sentences: first explains what the tool does, second explains its utility. No filler words, efficiently conveys purpose and usage context. Front-loads the key action ('Polymarket markets resolving...').
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 read-only tool with two parameters and no output schema, the description adequately covers purpose and usage. It could hint at output fields, but the context is sufficient for an agent given sibling tools like 'get_markets' likely share a similar output structure.
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. The description adds meaning by linking parameters to the use case ('resolving within next N hours' for hours, 'leading probability' for min_prob), providing semantic context beyond the schema.
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 clearly states the tool retrieves Polymarket markets resolving within a time window with a probability filter. It distinguishes itself from siblings like 'get_markets' and 'get_late_game_sports' by focusing on near-resolution arbitrage.
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 description explicitly mentions use cases: 'resolution arbitrage and last-minute positioning.' This provides context for when to use it, though it does not explicitly state when not to use it or name alternatives.
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.
Many tools are specialized, but several pairs have fuzzy boundaries: e.g., get_funding_rates vs get_top_funding_rates, get_basic_macro vs get_macro_context, get_simple_iv vs get_options_iv. An agent could easily select the wrong one.
Most tools follow a 'get_X' pattern with descriptive noun phrases. There are a few exceptions like 'create_api_key' and 'search_markets', but overall the convention is consistent and readable.
With 47 tools, the server is overloaded. While the domain is broad, this many tools makes discovery and selection difficult for an agent, reducing coherence.
The tool set covers an impressively wide range: macro data, funding, prediction markets, OI history, whale tracking, risk analytics, position sizing, backtesting, and signal generation. It leaves no obvious gaps for a crypto trading assistant.