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

The description explains certain output semantics (e.g., reverse_direction_conflict, preferred_direction derivation) which adds transparency about the meaning of fields. However, it does not disclose any side effects, permissions, rate limits, or error conditions. Since no annotations are provided, the description carries the full burden, and it only partially addresses behavioral aspects.

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 excessively long and repetitive, with dense technical jargon like 'W1-C1 standard object block' and long clauses about internal logic. It reads as a wall of text rather than a clear, structured summary. Key information is buried, and the description would benefit from a concise overview followed by details.

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?

The description is incomplete in that it does not cover input parameter usage or provide a clear usage context. It does explain some output field semantics, which helps, but the lack of guidance on when to use the tool and what the parameters mean leaves significant gaps. The description focuses excessively on output details while neglecting the overall context.

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?

The description does not explain any of the input parameters (symbol, tf, include_tfs). While the schema provides minimal examples (e.g., 'e.g. BTCUSDT'), the description adds zero value to parameter understanding. The schema coverage is 67% but only with examples, not meaningful descriptions. With no added clarification, parameter semantics are severely lacking.

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 states it provides an 'AI-synthesized market reading' with customer-facing language, which clearly identifies the tool's purpose. It distinguishes itself from raw data tools by mentioning 'Engine-native raw fields are NOT exposed here' and referencing alternatives like decker.get_market_state. However, the distinction is buried in verbose output details, so it's not maximally clear.

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 lacks explicit guidance on when to use this tool versus siblings. It mentions using 'the REST raw contract or decker.get_market_state' for raw fields, but that's about output content, not tool selection. There is no statement like 'use this when you need a customer-friendly summary' or 'use get_market_state for raw data.'

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