Server Quality Checklist

Tool Scores

• factor_analysisA
  4.3/5.0
  Behavior4/5

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

  Annotations already indicate read-only, non-destructive, and idempotent behavior. The description adds value by detailing the OLS regression process, factor interpretation, statistical significance thresholds, and the set of outputs (alpha, loadings, R-squared, residual vol). This goes beyond what annotations provide.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is concise and well-organized: it opens with the main action, breaks down factors, explains significance, lists outputs, and places the tool in context. Every sentence is informative with no redundancy.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity (statistical regression with multiple outputs), the description covers inputs, process, outputs, and usage scenario. The presence of an output schema (as indicated by context signals) reduces the need to detail return values, leaving the description sufficiently complete for an agent to invoke correctly.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100% and the equity_curve parameter is well-described with format, source, requirement, and example. The tool description does not add further parameter details beyond what the schema already provides, so a baseline of 3 is appropriate.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool decomposes returns into Fama-French factors using OLS regression, lists four factors, and explains alpha. It also specifies its place relative to siblings: 'Use this after backtest_strategy to understand WHERE your returns come from.' This distinguishes it from the sibling tools.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description explicitly directs usage after backtest_strategy and notes the requirement of at least 30 data points in the equity curve parameter description. It does not explicitly cover when not to use or contrast with screen_stocks, but the context is clear enough for typical use.

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

• backtest_strategyA
  4.5/5.0
  Behavior5/5

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

  Discloses key behaviors beyond annotations: fully deterministic, rebalance-loop engine, risk enforcement, and output details (equity curve, trade log, performance metrics). No contradiction 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Succinct and well-structured, with the main purpose front-loaded. Includes all necessary information without redundancy. Uses clear breaks for outputs and usage guidance.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the existence of an output schema, the description sufficiently covers return values and behavioral context. It explains the engine, determinism, and provides post-backtest guidance, making it complete for agent use.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100%, so the schema already documents all parameters adequately. The description adds no extra parameter-level information, meeting the baseline expectation.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool runs a historical backtest on a stock screening strategy, specifying the engine type, outputs, and determinism. It distinguishes from siblings like screen_stocks (screening) and factor_analysis (post-backtest decomposition).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  Provides guidance on when to use this tool (for backtesting) and a clear next step to use factor_analysis. However, it doesn't explicitly state when not to use it or mention alternatives for live trading.

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

• screen_stocksA
  4.5/5.0
  Behavior5/5

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

  Annotations already declare readOnlyHint=true and destructiveHint=false, and the description aligns by describing a read-only screening operation that returns results without side effects. The description adds context about the return format (ranked candidates with scores and metrics) and supported screen types and universes, going beyond what annotations provide.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is four sentences, front-loaded with the core action and output, followed by usage context and scope, and ending with guidance on next steps. Every sentence adds value with no redundancy or filler.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness5/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the existence of an output schema and complete schema descriptions, the description covers purpose, usage, scope, and follow-up tools. It provides sufficient context for an agent to understand when and how to use the tool.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters3/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 100%, meaning all parameters are already well-documented in the input schema with their types, defaults, and examples. The description does not add significant new information about parameters beyond the schema, so it meets the baseline expectation for a high-coverage schema.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose5/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description states the tool screens a stock universe with quantitative filters and returns ranked candidates. It clearly identifies the action (screen), resource (stock universe), and output (ranked candidates with scores). It also distinguishes from sibling tools by mentioning backtest_strategy and factor_analysis as follow-ups.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description explicitly says to use this tool to find stocks matching specific criteria, listing value, momentum, quality, or multi-factor. It provides guidance on what to do after screening (use backtest_strategy or factor_analysis). However, it does not explicitly state when not to use it or mention alternative tools for other tasks, though the context is clear.

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