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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=false, so safety and determinism are covered. The description adds the output shape (1-5 tier plus an AI parity vulnerability rating) and analytical factors, but says nothing about whether the scoring is a deterministic function of the inputs, whether it needs a live data source, or how to interpret borderline tiers.

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?

Two sentences, front-loaded with the output (score range) and followed by the analytical inputs. No filler, though the framework citation is the only element that occupies space without adding invocation guidance.

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 must carry return-value context, and it does partially (defensibility score 1-5, AI parity vulnerability). It omits the tier-to-meaning mapping and any statement of how the result should be used in a venture evaluation, leaving a gap for a scoring tool whose outputs are interpretive.

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 100%, so the baseline is 3. The description alludes to two inputs ('customer acquisition channels' and 'network effects / workflow lock-in'), but adds no format detail, scoring weights, or examples beyond what the schema already documents, including the enumerated business_model values.

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?

States a specific verb and resource: 'Calculates the defensibility score (1 to 5) and AI parity vulnerability for a startup.' It also names the analytical basis (Mode VC's Distribution Moat Framework), which clearly separates it from the retrieval siblings (search_investors, get_chart_data). It stops short of explicitly contrasting itself with the nearest sibling, get_mode_vc_thesis_and_criteria.

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 names no when-to-use condition, no prerequisites, and no alternatives. An agent cannot tell from this text whether the tool is meant to be called before, after, or instead of get_mode_vc_thesis_and_criteria, or whether inputs must be gathered elsewhere first.

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