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inject-guard

Untrusted-content guardrail for agents: submit a blob of text you are about to feed to your own LLM (scraped web content, a tool result, another agent's message) and get a machine-enforceable verdict - is this a prompt-injection / jailbreak / data-exfiltration / tool-hijack attempt? Returns a risk level, the detected classes with spans, the unicode obfuscation it found (zero-width, bidi-override, tag-chars, homoglyphs), and a SANITIZED copy safe to feed onward. Hybrid: a deterministic, uninjectable pattern engine (authoritative) plus an LLM classifier that can only raise the risk, never clear a flag. Detection of known injection classes - not a proof of safety. [security; up to 15c/call]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe untrusted text to scan before you feed it to your LLM.
contextNoOptional: where the content came from (url, tool name, sender) - context only.

TDQS

A4.8/5.0
Behavior5/5

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

The description thoroughly explains the tool's hybrid approach (deterministic pattern engine plus LLM classifier) and its behavioral traits: it can only raise risk, never clear a flag. It also states limitations ('not a proof of safety') and discloses cost. No annotations provided, so the description alone provides full transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is detailed and informative, but slightly verbose with phrases like 'Hybrid: a deterministic, uninjectable pattern engine (authoritative) plus an LLM classifier...' that could be streamlined. However, every sentence adds value, and the structure is logical.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description fully covers the return values: risk level, detected classes with spans, unicode obfuscation details, and a sanitized copy. It also mentions limitations and cost, making it complete for an AI agent to understand the tool's capabilities and response.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions for both parameters. The description reinforces the meaning of 'content' as untrusted text and 'context' as provenance information. While it doesn't add new technical details beyond the schema, it contextualizes their usage effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: to scan untrusted text for prompt injection and related attacks before feeding it to an LLM. It lists specific threat classes (prompt-injection, jailbreak, data-exfiltration, tool-hijack) and distinguishes itself from siblings like secret-scan or secure-code-review.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use the tool: 'submit a blob of text you are about to feed to your own LLM' and gives examples of sources (scraped web content, tool result, another agent's message). It implies when not to use it (not a general-purpose security scanner) and differentiates from 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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TDQS

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct security domain: prompt injection, secret scanning, code review, transaction safety, tool call safety, and x402 trust audit. Despite overlapping themes, their purposes are clearly differentiated by detailed descriptions.

Naming Consistency3/5

Tool names use a mix of patterns like verb-noun (inject-guard, sign-guard), noun-verb (secret-scan), and noun-noun (pr-summary, x402-trust-audit). The consistent use of lowercase and hyphens helps readability, but the lack of a uniform verb_noun pattern lowers consistency.

Tool Count5/5

Seven tools is a reasonable number for a security-focused server covering multiple guardrails and utilities. Each tool earns its place without overwhelming the agent.

Completeness4/5

The set covers core agent safety areas: input guardrails, secret detection, code review, transaction verification, and tool call safety. The inclusion of a PR summary tool is slightly out of scope, but overall coverage is strong with minor gaps like audit logging.

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