deep_analyze

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses that the tool is read-only, is not financial advice, is heavier (reads multiple timeframes and runs an event study), and describes a 'strictly causal event study' to indicate methodological rigor. It lacks explicit mention of rate limits or error behavior, but for a read-only market-data tool, this is adequate and adds meaningful context beyond the raw schema.

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 is well-structured: it opens with a clear purpose statement, uses a list to enumerate return contents, and follows with concise usage guidance and a default-behavior note. It is slightly verbose but every sentence adds useful information, and key details are front-loaded.

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 tool's complexity, the description covers its purpose, return contents, usage context, performance characteristics, and safety (read-only, not financial advice). The presence of an output schema means return values are already documented elsewhere. The main gap is parameter explanations, which are scored separately, so overall completeness is high for a heavy analysis tool.

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 description coverage is 0%, so the description must compensate for parameter meaning. It only explains the timeframes parameter default (1d/4h/1h ladder) and leaves horizon, exchange, and oscillator unexplained. An agent would not know what 'horizon' or 'oscillator' represent in this context, significantly hampering correct parameter usage.

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 performs a thorough, evidence-backed read of one symbol across multiple timeframes, listing specific outputs such as per-timeframe trend, momentum, statistical context, forward-return distribution, and a synthesized verdict. It distinguishes itself from sibling tools by naming lighter alternatives (compute_indicators, analyze_structure, detect_divergence) and positioning itself as the heavy, comprehensive option.

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 explicitly states when to use this tool ('when the user wants a thorough judgement', 'asks whether a setup is worth taking', 'analyze X deeply') and when not to ('quick one-value questions', recommends single-shot tools). It also names the lighter alternatives directly, providing unambiguous guidance for tool selection.

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