linkedin_score_lead

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

With no annotations, the description carries the behavioral disclosure burden. It adds useful detail about the scoring dimensions and the 100-point scale, showing what kind of computation is performed. However, it does not disclose the output format, whether the optional icp object replaces or supplements stored criteria, or any side effects.

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?

A single sentence that is concise, front-loaded, and free of filler. It immediately communicates the tool's purpose and distinguishing scoring framework.

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?

Despite a nested icp object, no output schema, and no annotations, the description is minimal. It lacks sibling differentiation, parameter context, output details, and any indication of whether pre-existing lead research or ICP configuration is required. An agent could easily confuse this with ranking or ICP-matching tools.

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 50%, and the description adds no parameter-level meaning. It does not explain that leadId is the lead/profile identifier nor clarify the role of the icp object in scoring. The schema partially documents properties, but the description fails to compensate for the remaining gaps.

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 identifies the action ('scores a lead'), the resource, and the exact scoring framework: '100-point Lead Scoring Engine (ICP Fit, Service Relevance, Authority, Signals)'. It is more specific than a vague 'score lead' statement, though it does not explicitly contrast itself with sibling tools like linkedin_rank_leads or linkedin_match_icp.

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 provides no guidance on when to use this tool versus alternatives such as linkedin_rank_leads, linkedin_match_icp, or linkedin_filter_leads. It implies single-lead scoring but does not state prerequisites, exclusions, or preferred use cases.

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