Get Lead Score

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

The description discloses a key behavior: that it internally reuses score_conversation's analysis before applying weighting. This gives the agent insight into the tool's internal mechanics. It also notes the repeat_caller param depends on external lookup, adding context. No annotations exist, so the description carries the burden, and it discloses the reuse behavior that would otherwise be invisible.

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?

Two concise sentences that state purpose, output, and the key relationship to the sibling tool. Efficient and front-loaded with the outcome. Could potentially clarify the weighting scheme, but no wasted words.

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 scoring tool with 5 params (4 required) and no output schema, the description communicates the core output (0-100 score, hot/warm/cold classification) and the internal pipeline. Missing return-format detail (e.g., does it return a JSON object, structured fields?) but given no output schema and moderate complexity, this is reasonably 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 80%, with descriptions on raw_outcome, call_duration, repeat_caller, and source_system. The tool description doesn't elaborate on parameter semantics beyond what the schema provides, but that's acceptable given high coverage. The behavior it adds about repeat_caller being externally determined aligns with the schema's note. Baseline 3 is appropriate.

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?

Clear verb+resource ('Score a call transcript 0-100 and classify it hot/warm/cold'). Describes what it does, what it returns, and explicitly distinguishes from sibling score_conversation by noting it 'Internally runs the same analysis' then applies 'point-based weighting'.

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 distinguishes from score_conversation by noting the internal reuse and additional weighting step, implying get_lead_score builds on the base scoring. However, it doesn't explicitly state when a user should choose this tool over score_conversation or diagnose_workflow_error, leaving some ambiguity about the decision.

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