ldbd_get_chart_indicators

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

With no annotations, the description carries the disclosure burden. It reveals the on-demand computation, publicly accessible nature, symbol coverage, and the edge case of short history returning a subset plus a 'missing' list. It lacks details on rate limits or response status semantics, but these are not critical for invocation.

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 dense yet every sentence contributes: it lists the exact indicator set, usage constraints (public, markets), output philosophy (data-only), and fallback behavior. No fluff or repetition; information is front-loaded with the core purpose.

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, but the description compensates by enumerating the computed indicators and explaining the short-history response (subset + 'missing' list). It does not specify the JSON structure or status field values, but a capable agent could parse the expected data from the list given.

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 input schema is well-covered (100%) with a clear symbol description and examples. The tool description adds value by specifying supported markets (US, KRX, crypto) and implicitly validating the symbol format, going slightly 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 opens with a clear verb+resource: 'Get technical indicators for an asset' and explicitly enumerates the indicators computed (moving-average ladder, RSI, volatility, etc.). This distinguishes it from sibling tools like ldbd_get_macro_indicators by scoping to chart/technical data.

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 provides concrete usage context: works for US/KRX/crypto symbols, requires no API key, and yields raw data without interpretation (the agent's job). However, it does not explicitly name alternative tools or state when NOT to use this tool, so it falls short of a 5.

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