compliance_fairness
[security] Fairness proof (FNS-100-FairnessBound)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| metric | Yes | ||
| model_id | Yes | ||
| dataset_id | Yes | ||
| protected_attrs | Yes |
[security] Fairness proof (FNS-100-FairnessBound)
| Name | Required | Description | Default |
|---|---|---|---|
| metric | Yes | ||
| model_id | Yes | ||
| dataset_id | Yes | ||
| protected_attrs | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description carries the full behavioral burden, and it discloses nothing: no permission requirements, no indication of whether a proof is computed, stored, or merely validated, no cost/latency hints, and no side-effect profile. Nothing beyond a two-word label is provided.
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 short but that brevity reflects under-specification rather than economy; there is no wasted sentence, but also no informative one. The single fragment is front-loaded only in the trivial sense of being one line.
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 four-parameter required tool with no annotations and no output schema, the definition supplies essentially no information an agent needs to invoke it correctly. It cannot determine valid metric values, the semantics of protected_attrs, or what the tool returns.
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?
Four required parameters (model_id, dataset_id, protected_attrs, metric) with 0% schema description coverage, and the description explains none of them. "metric" shows only a single example value (demographic_parity) with no enumeration of valid metrics, and protected_attrs' expected format is entirely undocumented.
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?
"Fairness proof (FNS-100-FairnessBound)" names a resource (fairness) and a standard identifier, but the name already says "fairness" and the tag "[security]" adds little. There is no verb, so an agent cannot tell whether this generates a proof, verifies one, or reports a metric, nor how it differs from compliance_check or compliance_transparency.
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 when-to-use, when-not-to-use, or prerequisite statements are given. The only implied guidance is the "[security]" tag and the FNS-100 reference, which hint at a compliance context but do not tell the agent when this tool is the right choice versus its many compliance_* and trust_* siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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