get_upcoming_catalystsLists upcoming market catalysts for an asset within a horizon: token unlocks, governance votes (Tally), ETF/SEC deadlines, FOMC dates. Helps agents avoid blind trades into known events. Free data sources (Tally + curated DB).
| Name | Required | Description | Default |
|---|---|---|---|
| asset | Yes | Asset ticker, e.g. "ARB", "SOL", "BTC" | |
| horizon_hours | No | Horizon in hours (default: 168 = 7 days, max: 720 = 30 days) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint (true). The description adds value by specifying data sources (Tally + curated DB) and listing the types of events covered. No contradictions 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 states purpose, second adds usage context and data sources. No filler, highly efficient, and front-loaded.
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?
The description covers purpose, usage, data sources, and event types. Missing output format details, but with only 2 simple parameters and no output schema, the description is fairly complete. Could mention what the returned list looks like.
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 does not add meaning beyond the schema: 'asset' and 'horizon_hours' are sufficiently documented in the schema, and the description only says 'within a horizon' without extra details.
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 lists upcoming market catalysts (token unlocks, governance votes, ETF/SEC deadlines, FOMC dates) for a given asset and horizon. This specific verb+resource combination distinguishes it from sibling tools like get_market_context or get_recent_news.
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 provides clear context: 'Helps agents avoid blind trades into known events.' This implies use before trading. However, it lacks explicit exclusions or when-not-to-use guidance, and no alternative tools are mentioned.
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.