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

Beyond the annotations (readOnlyHint=false, openWorldHint=true, non-idempotent, non-destructive), the description discloses the async contract ('Returns a run id right away') and the cost model (points at website rates, metered on models used). It does not cover failure/cancellation behavior, but it adds substantial value over the annotation set.

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?

Front-loads the core action and async/cost facts efficiently in a compact block, but the trailing parenthetical '(uses points, metered on the models used like the website)' duplicates the earlier 'Uses the account's points at the website's rates', which is minor waste.

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?

With no output schema, the description correctly explains the async return (run id) and the follow-up retrieval tool, and covers cost and agent composition for a 7-parameter tool. It is complete enough to invoke correctly, lacking only edge-case behavior.

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 coverage is 100%, so the baseline is 3, but the description goes further by explaining the semantic role of the four agents (indicator, intelligence, fundamental, decision) and pointing to list_models for the model override field, adding meaning beyond the raw schema.

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?

States a specific verb and resource ('Run SimianX's four live AI analysts once on a US stock or a crypto pair') and even enumerates the four agents and what each does. It also implicitly distinguishes itself from the sibling get_live_analysis by defining the run/poll split.

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?

It gives clear context: run this 'once' and collect results with get_live_analysis, and it warns that the tool consumes account points. It does not explicitly exclude alternatives like start_deep_analysis or autopilot tools, so routing among those siblings is left to inference.

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