What a $1,000 buy of a coin on Jan 1 of each available year would be worth today — ROI, peak value and date, and the maximum drawdown endured along the way. Real Binance data, refreshed daily.
| Name | Required | Description | Default |
|---|---|---|---|
| coin | Yes | Lower-case ticker, e.g. btc, eth, sol. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds that data is 'Real Binance data, refreshed daily,' which goes beyond the readOnlyHint annotation by indicating the data source and freshness. However, it does not disclose any limitations or additional behavioral traits like rate limits or error conditions.
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, front-loaded with the key outcome (what a $1,000 buy would be worth today) and additional details. Every sentence serves a purpose, with no wasted words.
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 tool with one parameter and no output schema, the description adequately explains the return values (ROI, peak, max drawdown) and data source. No missing information for effective invocation.
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%, and the description does not add new meaning to the coin parameter beyond the schema's 'Lower-case ticker' description. Baseline 3 is appropriate as the description adds no extra semantic value.
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 clearly states the tool computes buy-and-hold performance for a $1,000 investment on Jan 1 each year, including ROI, peak, and max drawdown. This is specific to the resource and verb, and distinct from sibling tools like get_dca or run_backtest.
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?
No explicit guidance on when to use this tool versus siblings such as get_dca or compare_strategies. The description implies a specific use case (buy-and-hold analysis) but does not provide context for alternative tools or exclusions.
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 has a clearly distinct purpose: statistical checks, strategy comparison, historical returns, live signals, DCA, overfitting index, strategy listing, dataset query, backtesting, Q&A search, and glossary. No overlap in functionality.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., check_overfitting, run_backtest, search_glossary). No mixing of conventions.
11 tools is well-scoped for a crypto backtesting server, covering the full workflow from strategy selection, backtesting, overfitting analysis, to educational queries without excess or deficiency.
The tool set covers core backtesting, overfitting diagnostics, data retrieval, and knowledge base searches. Minor gaps like strategy modification or saving results are present, but the main lifecycle is complete.
