Moltline Agent Governance & MCP Auditor

Injection Scan

injection_scan

Read-onlyIdempotent

Scan untrusted text for prompt-injection patterns before ingestion. FREE.

Use on any web page, email, or document an agent is about to ingest to catch prompt-injection and data-exfiltration patterns before they reach the agent's context. Typical input {"text": ""} returns {"injection_suspected": bool, "count": N, "hits": [{"line": N, "pattern": "...", "text": ""}], "note": "..."}.

Not for reviewing a skill file you control (audit_skill_file), and a clean result is not a guarantee of safety - it reports pattern matches only. Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": ""}. Every call is read-only and idempotent, so after correcting the input it is always safe to retry.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes	The untrusted content to scan, pasted as a single string.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.7/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds valuable detail: error handling (returns error object instead of protocol error), and the fact that the tool is safe to retry after correction. It also describes the return structure, which goes beyond annotations.

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

Conciseness5/5

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

The description is efficiently structured: it starts with the core purpose, then adds usage context, output format, limitations, and error behavior. Every sentence adds value with no redundancy, and it is front-loaded with the most critical information.

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?

Given the tool's simplicity (one parameter, output schema present) and comprehensive annotations, the description covers all aspects: when/why to use, input/output format, error handling, and limitations. It is fully adequate for an agent to use correctly.

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 description coverage is 100%, so baseline is 3. The description adds context by showing a typical input example and describing the output format, which helps the agent understand how to structure calls and interpret results.

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 explicitly states the tool scans untrusted text for prompt-injection patterns before ingestion. It clearly differentiates from the sibling tool audit_skill_file by specifying 'Not for reviewing a skill file you control'.

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 provides clear guidance: use on any untrusted web page, email, or document before ingestion. It also explicitly states when not to use (audit_skill_file) and warns that a clean result is not a guarantee of safety, setting proper expectations.

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

A4.4/5.0

Disambiguation5/5

Every tool has a clearly distinct purpose targeting a different aspect of agent governance: domain readiness, config auditing, skill file auditing, injection scanning, inventory, blast radius scoring, policy generation, and persona loading. Each description explicitly states what the tool is not for, eliminating ambiguity.

Naming Consistency2/5

Naming is inconsistent: some tools start with a verb (audit_mcp_config, get_auditor_persona), others with a noun (agent_readiness_scan, injection_scan, inventory_report, scope_check), and governance_policy is a plain noun phrase with no verb. There is no predictable pattern across the set.

Tool Count5/5

8 tools is well-scoped for the domain of agent governance and auditing. Each tool serves a distinct and necessary function without redundancy, covering readiness, configuration, skill files, injection, inventory, permissions, policy, and persona.

Completeness4/5

The tool surface covers the major governance activities: audit, scan, inventory, policy generation, and blast radius. A minor gap is the lack of a tool to verify compliance against a generated policy, but the existing audit tools can be used for that purpose.

Resources

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