Compare semantic NC changes to an approved baseline and rank risks for focused human review.
Risk-rank semantic NC changes against an approved baseline for human review
| Name | Required | Description | Default |
|---|---|---|---|
| after | Yes | ||
| before | Yes | ||
| displayLimit | No |
| Name | Required | Description | Default |
|---|---|---|---|
| ok | Yes | ||
| data | No | ||
| live | No | ||
| tool | Yes | ||
| error | No | ||
| receipt | No | ||
| documentRevision | No | ||
| operationFingerprint | No |
Changes observed during successful MCP inspections.
v0.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive behavior, so the description only needs to add context beyond that. It adds the semantic scope and the 'human review' purpose, which is useful, but it does not describe specific behavioral details such as output shape, ordering, or how displayLimit affects results.
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 description is a single, tightly packed sentence with no filler. The main verb and core object are front-loaded, and every word adds meaning.
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?
The output schema covers return values and annotations cover side effects, but several gaps remain: `displayLimit` semantics are absent, parameter mapping from description to schema is only implicit, and the description does not explicitly disambiguate this tool from closely related siblings like compare_nc_files or analyze_nc_program.
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 for undocumented parameters. It indirectly maps 'baseline' to `before` and 'changes' to `after`, but it never explicitly describes either parameter, and `displayLimit` is entirely unexplained.
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 uses a specific verb ('risk-rank') and a precise object ('semantic NC changes') scoped to an 'approved baseline' and intended purpose ('human review'). This clearly differentiates it from sibling tools like compare_nc_files or analyze_nc_program, which perform related but different tasks.
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 a clear use case: run this when there are semantic NC changes to be risk-ranked against an approved baseline for human review. It does not explicitly name alternatives or state when not to use it, but the context is discernible enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.