demo_auditRuns the scanner on a small built-in bad-bot sample and returns the findings. Free; no x402 payment.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| demo | Yes | ||
| findings | Yes | ||
| signalCount | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": false,
+ "properties": {
+ "demo": {
+ "type": "boolean"
+ },
+ "findings": {
+ "items": {
+ "additionalProperties": {},
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "signalCount": {
+ "type": "integer"
+ }
+ },
+ "required": [
+ "demo",
+ "signalCount",
+ "findings"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds useful context beyond those: it uses a built-in sample, requires no payment, and returns findings. This complements the annotations without contradicting them.
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 short sentences deliver the core behavior first and the free/no-payment detail second. There is no wasted wording, and the most decision-relevant information is front-loaded.
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 parameters, a rich annotation set, and an output schema present, the description covers everything an agent needs: what the tool does, that it uses a fixed sample, and that it is free. Nothing essential is missing.
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?
The tool has zero parameters and an empty input schema, so there are no parameter semantics to document. The description reinforces that no input is needed by referring to a built-in sample, which is sufficient.
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 states a specific verb and resource: it runs the scanner on a small built-in bad-bot sample and returns findings. It clearly distinguishes itself from the sibling audit_bot_code by being a free, fixed-sample demo rather than a real audit.
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 clearly conveys when to use the tool: when you want a free, no-payment demonstration on a fixed sample. It does not explicitly name alternatives or exclusions, but the 'demo' framing and 'no x402 payment' make the intended usage context clear.
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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