Jesse MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While it mentions the return value ('Detailed improvement recommendations with expected impact'), it fails to disclose whether this is a read-only analysis, what data sources it queries (backtest vs live), computational cost, or any side effects. The phrase 'Analyzes current performance' is vague about the data source.

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?

The description follows a clear structured format with summary sentence, Args section, and Returns section. It is appropriately sized at three sentences plus structured metadata. No sentences feel wasted, though the Args/Returns sections duplicate what should ideally be in the schema (but aren't), making their inclusion here necessary rather than redundant.

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?

Given that an output schema exists (indicated by context signals), the description adequately covers the return value concept ('Detailed improvement recommendations'). However, for a 2-parameter analytical tool with no annotations, it lacks context about data requirements (does it need existing backtests?) and scope limitations, leaving gaps in the agent's understanding of prerequisites.

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?

With 0% schema description coverage, the description effectively compensates by documenting both parameters in the 'Args' section: 'strategy_name: Name of the strategy to analyze' and 'pair: Trading pair to test on (e.g., 'BTCUSDT')'. It provides a concrete example for the pair parameter, adding value beyond the raw schema types.

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 'Get[s] specific improvement suggestions for a trading strategy' and 'Analyzes current performance and recommends concrete changes.' It identifies the verb (suggest/analyze) and resource (trading strategy) clearly. However, it does not explicitly differentiate from similar siblings like 'strategy_refine' or 'strategy_analyze_optimization_impact', leaving some ambiguity about when to choose this over alternatives.

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 no guidance on when to use this tool versus alternatives like 'strategy_refine' or 'strategy_optimize_pair_selection'. It does not mention prerequisites (e.g., whether the strategy needs prior backtesting data or live trading history) or conditions where this tool might not be appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.