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

Annotations already declare readOnlyHint=true and openWorldHint=true, but the description goes well beyond them: it warns that context_coverage may mark sections complete/truncated/unavailable/unknown, that missing sections are not evidence of absence, that bounded lists must not be called exhaustive, and that the linkedin_thread_identity type is gated and returns only a public profile mapping. These are non-obvious behavioral caveats an agent would otherwise guess wrong.

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 front-loaded with the default behavior, which is good, but the 'When to use' section largely restates the opening paragraph ('Defaults to an account' and 'Prefer this over search_*' both appear twice), and the LinkedIn branches make the block long. The content earns its place individually, but the duplication costs structure points.

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 six-parameter, multi-mode, read-only tool with an output schema already covering return values, the description supplies the routing logic, the per-type behavior, the ambiguity-handling flow, and the coverage caveats. Nothing an agent needs to invoke it correctly is missing.

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 schema already documents all six parameters, but the description adds real semantic value: account_id as an alias for {type:'account', id}, that linkedin_url never resolves by name and returns candidates on ambiguity, and the multi-step flows for linkedin_conversation and linkedin_thread_identity.

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 gives a specific verb and resource ('Single-call bounded context for reasoning about a record') and enumerates exactly what comes back for the default account case (account row with ARR/lifecycle/renewal, subscriptions, 90 days of subscription_events, open opportunities, contacts, touches, tasks, notes). It also clearly distinguishes itself from siblings by naming search_* as the alternative it replaces.

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 states when to use it ('When the user asks anything broad about a record'), names the alternative ('Prefer this over individual search_* calls'), and gives a concrete trigger example ('tell me everything about Acme'). Per-type routing (account_id vs type+id) and the LinkedIn special cases are also spelled out.

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