find_effects

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'causal chains' but does not specify what the output looks like, how chains are represented, whether the graph direction is respected, or any side effects. Important behavioral traits like computational cost or prerequisites for using the parameters are missing.

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 highly concise: one sentence plus a counterpart reference. It front-loads the core purpose efficiently. However, it could be slightly expanded without becoming verbose to improve parameter understanding, but given its length, it earns a high score for conciseness.

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 the tool's complexity (finding causal chains in a graph), the description is too sparse. It lacks information on what defines a causal chain, how the graph is traversed, the role and default of maxDepth, and the return format. With no output schema and no annotations, the agent is left with insufficient context to invoke the tool effectively.

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 description coverage is 0%, meaning the schema itself provides no parameter descriptions. The description mentions 'cause' and 'candidates' implicitly but does not explain their meaning or format. The 'maxDepth' parameter is not mentioned at all, leaving the agent to infer its purpose from context. This is insufficient for correct usage.

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 states the verb 'find', the resource 'causal chains', and the scope 'starting at the named cause and reaching any candidate effect'. It also distinguishes itself from the sibling tool 'find_causes' by noting it as the symmetric counterpart, making its purpose 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?

The description explicitly identifies the symmetric counterpart 'find_causes', giving the agent clear guidance on when to use this tool (to find effects from a cause) versus its alternative. It does not include explicit when-not-to-use conditions, but the contrast is sufficient for differentiation.

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