Check untrusted text for prompt injection before use, using patterns and learned antibodies. Return allow status, attack class, risk, and reason.
Check untrusted text for prompt injection using patterns and learned antibodies. Returns allow, attack_class, risk and reason.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| tool | No | Optional tool name, e.g. shell |
Changes observed during successful MCP inspections.
v0.2.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It reveals the mechanism (patterns plus learned antibodies) and names the returned fields, but says nothing about side effects (is check-in only?), latency, false-positive/negative behavior, or what 'risk' and 'attack_class' values look like — thin for a safety-critical tool with zero annotation coverage.
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, zero filler, with the purpose front-loaded and the return contract immediately after. Everything stated is load-bearing, especially given there is no output schema.
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?
Naming the four return fields partly compensates for the absent output schema, and the mechanism hints at how judgments are made. But with no annotations and no description of the optional 'tool' parameter's effect or the meaning of 'risk'/'attack_class' values, an agent still lacks what it needs to interpret results reliably.
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 description never mentions either parameter; the only semantic anchor is the schema's own note that 'tool' is an optional tool name like 'shell'. With coverage at 50%, the description should explain that 'tool' scopes detection context and what happens if it is omitted, but it adds nothing beyond the schema.
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 ('Check untrusted text for prompt injection') plus the mechanism ('patterns and learned antibodies'), which is far more informative than the name alone. It is clearly distinct from trust_add_antibody, trust_stats, and trust_demo, but it never contrasts itself with trust_verify_claims, which an agent could plausibly confuse with injection scanning.
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?
Usage is only implied by the qualifier 'untrusted text' — an agent can infer it should be run before acting on external content. There is no explicit when-to-use/when-not statement, no prerequisite or threshold guidance, and no mention of the sibling tools as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.