compute_barrier

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

With no annotations provided, the description carries the full burden. It discloses the input-to-output relationship and the exact output shape, but it does not reveal which end of the 0-24 scale indicates a high barrier, what thresholds map to each label, or how omitted optional parameters (serpNoise, adjacentCompetitorCount) affect the result. Honest but incomplete.

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?

A single dense sentence with zero filler. The output contract and input sources are front-loaded, and every element carries information — no wasted words.

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?

Since there is no output schema, the description does need to explain the return value, and it does state the score range and labels. However, it omits interpretation guidance — whether a high barrier_score is favorable, what the labels mean in decision terms, and what happens at boundary inputs. Adequate as an API contract but thin on context.

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 0%, so the description must compensate. It partially does by mapping 'competitor counts' to the two count parameters and 'SERP noise fraction' to serpNoise. However, it does not clarify the relative roles or weights of direct vs adjacent competitors, nor the meaning of the serpNoise fraction in the computation.

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 ('Compute'), a precise resource (barrier_score), the output contract (0-24 score plus a four-value label set), and the inputs (competitor counts + SERP noise fraction). This clearly differentiates it from the 20 sibling compute_* tools, which all target different metrics.

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?

No guidance is given on when to use this tool vs alternatives such as compute_multi_source_tam or compute_dealbreakers_v2. In a sibling group of 20 similar compute_* tools, the description provides no routing context, no prerequisites, and no exclusion criteria.

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