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

With no annotations, the description does the disclosure work: it states the server re-runs validation (`Re-runs test_formula itself server-side first`), trusts no stale result, only saves on validated, persists privately to the user's dashboard, and requires a Pro key. It does not describe overwrite/duplicate behavior or failure response, but the main side effects are disclosed.

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?

Five purposeful sentences introduce the action, then validation behavior, then param mapping; no padding. The structure packs much detail into a continuous paragraph and would be slightly clearer with bullet/list separation of parameter groups, but it remains efficient.

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 annotations, an output schema, and 7 params, the description covers operation, conditions, side effects, auth, privacy, and parameter relationships. The only notable omissions are precise error/invalid-verdict behavior and detailed semantics of `horizon`, but the output schema and sibling `test_formula` fill some gaps.

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 0%, but the description enumerates the main params: `symbol`/`formula`, conditional use of `horizon` vs `horizon_bars` based on `timeframe`, meaning of `hours`, and optional `label`. It leaves precise semantics of `horizon` (e.g. `ret_30s_bp`) to defaults/sibling knowledge but sufficiently compensates for an empty 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?

Description states the action (`Save a formula as a strategy`) and the condition (`IF it currently validates`), clearly distinguishing it from testing-only siblings by describing persistence to dashboard. It names sibling `test_formula` and clarifies save happens only after fresh validation, so the function's purpose is unambiguous.

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 clearly implies usage as the persistence counterpart to `test_formula` by saying it re-runs the test server-side and only saves on a fresh 'validated' verdict. It also supplies prerequisites (`EnsoTrade Pro API key`) and privacy scope. It does not explicitly spell out cases to prefer `test_formula` over `save_strategy` (e.g., testing without persisting), so not a full 5.

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