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

Annotations only carry readOnly=false and destructive=true; the description goes much further, disclosing the exact cost model (0.07 credits/profile, charged only for profiles found), background execution, the free skip of already-enriched profiles, and the required user-consent two-call pattern. It also tells the agent what happens when credits run short. Nothing here contradicts the destructive/openWorld hints.

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?

It is a long description, but the purpose and the cost/consent constraint are front-loaded, and each paragraph adds actionable information rather than filler. A few parenthetical asides could be trimmed, keeping it just short of a 5.

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?

With no output schema, the description closes the loop by directing the agent to get_enriched_profiles (or re-reading get_signal_leads) for results, and it covers cost, consent, idempotency, and credit exhaustion. For a paid, background, write-like enrichment call, an agent has everything needed to invoke it 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?

Schema coverage is 100%, so the structured fields already document all three parameters and the baseline is 3. The description nonetheless adds real meaning: it explains that confirm:false is a no-charge estimate and confirm:true is the queued commitment, and that forceReenrich controls whether already-enriched profiles are re-billed — semantics beyond the schema text.

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 names a specific verb+resource ('Enrich LinkedIn profiles') and enumerates the exact attributes added (location, current company, headline/seniority, experience, skills), so its output is unmistakable. It is also distinguishable from sibling enrichment tools (enrich_contact_email, enrich_linkedin_urls) because it states the profile-level scope and the downstream purpose (filtering/segmenting/ICP scoring).

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?

It explicitly says when to use it and where the inputs come from ('pass the linkedinUrl values from get_signal_leads ... social listening engagers, or a list the user gives you'), and names the companion read tool (get_enriched_profiles) for retrieving results. The confirm:false-then-true workflow and the credits top-up escape hatch are spelled out as operating procedure.

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