The Clearing — The Lantern & Consensual Agent Lab

audit_gateway_payload_defense

Offline defensive analyzer for gateway prompts/logs. Detects parasitic catalog ETL delimiters, coined GGUF echoes, CUA tool schemas, and policy-violating CAPTCHA probes without emitting any honeytokens.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "payload": "<payload>"
    },
    "name": "audit_gateway_payload_defense"
  }
}

Input Schema

Name	Required	Description	Default
`payload`	Yes	Raw request body, catalog excerpt, or prompt text to inspect offline.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 14, 2026

TDQS

C2.5/5.0

Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It adds useful traits such as being offline and not emitting honeytokens, but it does not clarify whether it logs, mutates state, has rate limits, or what the analysis returns.

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

Conciseness3/5

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

It is only two sentences and front-loads the general purpose, so it is not bloated. But the second sentence is a dense list of opaque jargon that reduces clarity rather than efficiently earning its place.

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

Completeness2/5

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

This is a simple one-parameter analyzer with no output schema and no annotations, so the description should explain what a detection result looks like and how findings are returned. It does not, leaving an agent unable to predict the tool's output or practical scope.

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

Parameters3/5

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

Schema description coverage is 100% for the single payload parameter, so the schema already explains it. The description only reinforces that the payload is inspected offline and adds no syntax, format, or example detail beyond the schema.

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

Purpose3/5

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

The description identifies a specific resource and action: an offline defensive analyzer for gateway prompts/logs. However, the detection categories are dense jargon ("parasitic catalog ETL delimiters," "coined GGUF echoes," "CUA tool schemas") that obscure what it actually detects, and it does not distinguish itself explicitly from audit-oriented siblings.

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

Usage Guidelines2/5

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

It implies an offline analysis context but gives no guidance on when to use this tool versus the many audit_* or inspect_* siblings. There are no exclusions, prerequisites, or alternative selections.

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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