linkedin_match_icp

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

No annotations are provided, so the description must carry the full behavioral burden. It states that the tool evaluates fit and provides confidence scoring, but it does not disclose whether the operation is read-only, what the output format or score range is, how optional 'icp' is handled, or what happens when no ICP is supplied. This leaves meaningful behavioral gaps.

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 that front-loads the core action and includes a useful outcome detail ('confidence scoring'). It is appropriately concise, though it sacrifices some necessary context about behavior and usage.

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 absence of annotations, the lack of an output schema, and the presence of an optional nested ICP object, the description should explain more: expected return value, behavior when 'icp' is omitted, and how this differs from overlapping siblings. The current description is too minimal for an agent to invoke the tool confidently in ambiguous situations.

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 provides 100% parameter coverage with descriptions for 'leadId' and the nested ICP fields, so the baseline is 3. The description adds no specific parameter-level detail beyond naming 'custom Ideal Customer Profile rules', which does not exceed what the schema already communicates.

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 a specific action ('Evaluates lead fit'), the object ('lead'), and the criteria ('custom Ideal Customer Profile rules'), plus a distinguishing output feature ('confidence scoring'). However, it does not differentiate this tool from the similarly named sibling 'linkedin_score_lead', so it stops short of a 5.

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?

There is no guidance on when to use this tool versus alternatives like 'linkedin_score_lead', 'linkedin_filter_leads', or 'linkedin_rank_leads'. The description implies usage for ICP-based evaluation but provides no explicit context, exclusions, or alternative routing.

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