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

No annotations provided, so description carries full burden. It describes outputs (open type, levels, scenario) but does not disclose side effects, data freshness, or authorization requirements. Adequate for a read-only analysis tool but leaves behavioral assumptions unstated.

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?

Two concise, front-loaded sentences. Every word adds value: purpose, outputs, example queries. No redundancy or fluff.

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 no output schema, description adequately explains return values (open location, type, key levels, scenario) but lacks precise structure or data types. Sufficient for a workflow tool with extensive sibling list; minor gaps in depth.

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 covers all 7 parameters with descriptions (100% coverage). The description adds no new parameter-level meaning beyond the schema; e.g., 'value_area_rule' details are already in schema. Credit for schema coverage keeps baseline at 3.

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?

Description clearly states tool performs 'Market Profile open analysis' and lists specific outputs (open location, open type, key levels, scenario framing). Provides concrete use examples ('how did BTC open today?'), establishing a distinct purpose from sibling tools like run_session_structure.

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?

Explicitly states use cases ('Use for...') and provides example queries. Does not explicitly state when not to use or list alternatives, but context implies differentiation from siblings. Lacks explicit exclusion criteria, so not a 5.

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