list_ingested_data

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds minimal behavioral context. It does state 'List all' implying comprehensive results without filtering, but does not mention pagination, limits, or sorting. Given the strong annotations, a score of 3 is appropriate.

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 two sentences long with no fluff. It front-loads the purpose and provides a succinct summary of what the tool does. Every word is necessary.

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, the description adequately explains that the output lists specific types of ingested data. However, it could be more precise about the output format or any limitations (e.g., if the list is limited to a certain number). Still, it is largely sufficient for a simple list tool.

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?

There are zero parameters, and schema coverage is trivially 100%. According to the rules, 0 parameters get a baseline of 4. The description adds no parameter information, which is acceptable since there are none to document.

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 clearly specifies the verb 'List' and the resource types: custom OHLCV datasets, signal files, Onyx document ingestions, and registered strategies. It also adds context by stating it shows proprietary data brought into AlgoChains, distinctly setting it apart from sibling list tools.

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 description clearly implies that this tool is for listing ingested data types, and sibling tools cover other entities (e.g., list_skills, list_polymarket_markets). It provides clear context on what it lists but does not explicitly state when not to use it or mention alternatives.

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