trace_data_flow

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal an important behavioral trait: it 'clearly separates observation from inferred flow,' indicating the output distinguishes empirical data from inference. However, it does not mention side effects, permissions, failure modes, return structure, or caveats, so transparency is only partial.

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 a single, well-structured sentence. It front-loads the core verb and target ('Traces observed remote and persistence participants') and adds a meaningful nuance in the subordinate clause ('clearly separating observation from inferred flow'). Every word earns its place, with no fluff or redundancy.

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?

For a tool with three parameters and no output schema, the description gives a reasonable overview but leaves key invocation details unresolved. It does not explain what the trace output looks like, how 'limit' caps results, what 'include_related' changes, or what constitutes 'flow.' This is adequate but leaves clear gaps for an agent that must invoke the tool correctly.

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 already describes all three parameters with 100% coverage. The description aligns with 'variable_name' by saying 'for a state name' but adds no extra meaning for 'limit' or 'include_related.' Per the rubric, baseline 3 is appropriate given high schema coverage.

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 uses a specific verb 'Traces' and names the exact resource: 'observed remote and persistence participants for a state name.' The clause 'clearly separating observation from inferred flow' adds a distinctive functional scope, differentiating it from broader dependency/tracing sibling tools. It is neither tautological nor vague.

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 implies that the tool is used for tracing state-related data flow, but it provides no explicit when-to-use guidance, no comparison with alternatives like find_dependencies or impact_analysis, and no exclusions. In the presence of many siblings, this lack of context leaves the agent to guess when this tool is preferred.

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