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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower, and the description goes well beyond them: it details exactly what a free tier returns (first 5 rows, locked.count/locked.by_type), what is never returned (contact values, decision-maker names), and that withholding is surfaced via `entitlement` and `locked`. That is genuinely useful behavioral context an agent cannot get from the schema.

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 content is a single sprawling, comma-heavy sentence followed by a dense access paragraph. The audience qualifier is front-loaded, but the matching logic is buried mid-sentence and the length is driven by entitlement boilerplate rather than tool-selection signal.

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 does carry return-value burden and explains the locked/entitlement envelope and 'returns the behaviour it reasoned from.' However, the actual match semantics (what counts as a match, how 'demonstrated behaviour' is derived) remain vague, leaving an agent without enough to predict results confidently.

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 only 50%: dfx_id is documented in the schema, but `limit` is not explained anywhere. The description's audience list loosely hints at the dfx_id entity types but adds no constraint, default, or interaction detail for either parameter, so it fails to compensate for the coverage gap.

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?

It identifies an audience (family office, sponsor, capital provider, venture firm) and describes matching opportunities from 'demonstrated behaviour,' which gives a general sense of a recommendation/match tool. But the core verb+resource is buried in a run-on sentence, and it does nothing to distinguish itself from close siblings like search_opportunities, search_forward_opportunities, search_isi_opportunities, or search_vc_opportunities.

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 implies context (an investor wants matched opportunities) but gives no explicit when-to-use or when-not-to-use guidance and names no alternative among the many overlapping opportunity-search siblings. The only routing-like content is the access/entitlement explanation, which is about output, not selection.

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