Search Noon Barbari's trading glossary for a plain-language definition of an indicator, metric or concept (RSI, MACD, Sharpe ratio, drawdown, walk-forward, overfitting, and 60+ more). Returns the top matching terms with a short definition, the full explanation, and a link.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | A term or question, e.g. 'deflated sharpe' or 'what is RSI'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Adds behavioral context beyond annotations: returns top matching terms, short + full definitions, and link. Mentions glossary size (60+ terms). 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 with no redundant information. Front-loaded purpose, then returns format. Every word adds value.
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 search tool with 1 parameter and no output schema, description fully covers purpose, scope, return structure, and examples. Complete.
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 parameter description is clear. Description does not add new info about the parameter beyond the schema, but baseline 3 is appropriate.
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 uses specific verb 'Search' and resource 'glossary', provides examples (RSI, MACD, Sharpe ratio) and scope (plain-language definitions). Clearly distinguishes from siblings like search_answers and 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?
Implies usage for glossary definitions of trading terms but doesn't explicitly state when to use vs alternatives or when not to use.
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.
