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scrub_env

Read-only

Scrub a .env file into a safe .env.example: every value is blanked or replaced with a placeholder that keeps its shape (postgres://USER:PASSWORD@HOST/DB). Returns the example, the secrets found (AWS, GitHub, Stripe, Slack, Google, OpenAI, Anthropic, Resend, SendGrid, Twilio, Cloudflare, JWTs, private keys, database URLs, high-entropy strings) by key, kind and line with only the first 4 characters and the length, and findings for duplicate keys, non-UPPER_SNAKE names, unbalanced quotes, export prefixes and trailing spaces.

Input Schema

NameRequiredDescriptionDefault
textYesThe .env file contents. Free tier: 20,000 chars.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already declare a safe read-only, non-destructive operation, and the description goes well beyond them: it explains exactly how values are mutated (blanked or shape-preserving placeholders), what the return payload contains, and the privacy-conscious truncation to 'first 4 characters and the length'. That level of disclosure about output content and secret handling is exactly the added value structured fields do not provide.

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 dense sentences, front-loaded with the core transformation before the return details. The long provider enumeration is informative rather than wasteful, though it makes the second sentence heavy and could be compressed.

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 present, the description carries the full burden of explaining return values and does so thoroughly: the example output, the secrets structure (key, kind, line, truncated value), and the separate findings list. An agent has everything needed to call and interpret results.

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?

There is a single parameter whose schema description already covers it at 100% (including the free-tier char limit). The description adds no syntax, format, or constraint detail beyond the schema, so the baseline 3 for a fully documented schema is correct.

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?

States a specific verb and resource (scrub a .env file) plus the concrete output form (.env.example), and the placeholder example 'postgres://USER:PASSWORD@HOST/DB' makes the transformation unambiguous. No sibling in the list does anything similar, so the agent can route to it without opening any schema.

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

Usage Guidelines3/5

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

The purpose implies the use case (turning a real .env into a shareable example), but there is no explicit when-to-use statement, no prerequisites, and no named alternatives or exclusions. Usage is only inferable from the description of what the tool does.

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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