get_key_levels

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

With no annotations to rely on, the description carries full responsibility for behavioral disclosure. It discloses what is included (level-named plots, horizontal lines, box/zone edges, label prices), what is excluded (oscillator panes, generic OHLC mirrors), that results are tagged with source indicator, and that output is sorted by distance from current price. This is rich, specific behavioral context beyond a bare 'get' statement.

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?

Four purposeful sentences, each earning its place: scope definition with examples, explicit exclusions, ordering behavior, and usage guidance versus alternatives. The most decision-relevant information is front-loaded, and there is no fluff or repetition.

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?

No output schema exists, so the description must convey output nature. It does: levels are tagged with source indicator and sorted by distance. It also covers inclusion criteria, exclusions, and the alternative approach. Minor gaps remain, such as not explicitly stating the return type (e.g., array/table) or behavior when no levels are found, but for a read-only aggregation tool this is largely complete.

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% with individual parameter descriptions already present, so the baseline is 3. The description adds conceptual context like 'near the current price' for range_percent and clarifies what 'level-named' means (relevant to include_all_plots), but it does not add syntax, formatting, or behavior details that go substantially beyond the 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?

The description states a precise verb ('Aggregate') and a specific resource ('key price levels near the current price from ALL price-scale indicators'), and further details what counts as a level (S/R, pivot, VWAP, bands, BOS/CHoCH, horizontal lines, box/zone edges, label prices). It also explicitly contrasts this with manually combining get_indicator_values and get_indicator_graphics, making the tool's purpose unmistakable among siblings.

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 final sentence directly prescribes the use case: 'Use this instead of manually combining get_indicator_values and get_indicator_graphics when you need a support/resistance table.' This is an explicit when-to-use statement that names the alternative approach it replaces. The exclusion of oscillator panes and generic value plots further clarifies what the tool is optimized for.

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