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. It successfully documents what analysis is returned (trade metrics, risk summary) but fails to disclose safety characteristics (read-only vs destructive), performance characteristics, or side effects. It adds value by describing the analysis content but lacks operational behavioral traits.

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?

Well-structured with clear bullet points for output categories and a numbered workflow. Front-loaded with purpose and input/output contract. Minor fluff ('deep insights', 'understand what happened') prevents a 5, but overall efficient with no wasted sentences.

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 the moderate complexity (5 parameters, nested objects, output schema exists), the description provides strong workflow integration and sibling context but insufficient parameter documentation. The output schema exists so detailed return value explanation isn't required, but with 0% schema coverage on inputs, the description should have documented the optional flags.

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 must compensate significantly. It only mentions 'backtest result dict' (covering the required parameter) but completely omits the 4 optional parameters: analysis_type, include_trade_analysis, include_correlation, and include_monte_carlo. There is no mapping between the described analysis features and the boolean flags that control them.

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 extracts insights from backtest results, specifying the input (backtest result dict) and output (trade metrics, performance breakdown, risk metrics). It effectively distinguishes itself from sibling tools like 'optimization_run' or 'backtest_monte_carlo' by positioning itself as the analytical step that follows backtesting.

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?

Excellent explicit guidance with 'Use this after backtest()' and a numbered workflow (1. backtest -> 2. analyze_results -> 3. monte_carlo -> 4. risk_report). This clearly establishes when to use the tool versus alternatives and prerequisites, directly addressing the common workflow sequence.

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