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Glama
Jimil-Joshi

BlastRadius MCP

inspect_payload_dlp

Detects, reports, and redacts API keys, passwords, JWTs, cloud credentials, credit cards, SSNs, and PII in prompts, code, or logs to prevent data loss.

Instructions

Deep Data Loss Prevention (DLP) scanner. Detects, reports, and redacts API keys, passwords, JWTs, cloud credentials, credit cards, SSNs, and PII from prompts, code, and logs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentYesThe raw text, code snippet, or log output to inspect.
maskSensitiveNoWhether to return a sanitized version with credentials and PII masked.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It mentions detection, reporting, and redaction, but does not disclose whether the operation is read-only, whether it modifies the input, any authentication needs, or rate limits. The default maskSensitive=true behavior is only described in the schema.

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?

Two concise sentences with the purpose front-loaded. The list of detectable data types is long but informative and earns its place. There is no wasted wording.

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

Completeness3/5

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

With no annotations and no output schema, the description should ideally explain the return value (findings format, redacted output) and safety posture. It covers purpose and inputs but leaves output expectations and behavioral constraints unclear, making it only minimally complete for correct invocation.

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%, so both parameters (content and maskSensitive) are fully documented in the schema. The description adds no additional meaning or syntax beyond what the schema already provides, so the baseline of 3 applies.

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

Purpose4/5

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

States a clear verb (scanner) and resource (payload for DLP) and enumerates specific sensitive data types it handles. It does not explicitly differentiate from sibling tools like get_security_posture or verify_audit_log, but the payload-inspection focus is distinctive enough for an agent to identify it.

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?

No explicit when-to-use or when-not-to-use guidance, and no alternatives are named. The description implies usage for scanning prompts, code, and logs, but leaves the agent to infer when to call this versus the other security tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.