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generate_example

Propose a safe .env.example by scanning a folder and listing every environment variable with type hints, secret flags, code read locations, and browser-exposure warnings, without writing values.

Instructions

Propose a safe .env.example as text (one section per env root). It lists every variable seen in env files, templates and source code, each with a type hint, whether it looks secret, where the code reads it, and a warning if a secret would be exposed to the browser. Every line is NAME= with nothing after the equals sign: no value, not even from your templates. Nothing is written to disk; paste or save the text yourself.

path: folder to scan.

Input Schema

NameRequiredDescriptionDefault
pathNo.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: nothing is written to disk, every line is emitted as empty `NAME=`, no values are ever included even from templates, and secret-exposure-to-browser cases get a warning. Missing only secondary details such as behavior on an unreadable or missing path or scan cost on large repos.

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 key guarantee (safe, empty-value text output) is front-loaded in the first sentence, followed by the content spec and the no-disk-write caveat. Structure is good; the trailing 'path: folder to scan.' line is a slightly tacked-on fragment rather than integrated prose.

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

Completeness4/5

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

An output schema exists, so the description need not explain return values, and it instead specifies the output's invariant shape (empty `NAME=` lines, per-root sections) plus warnings. For a single-parameter read-only generator this is nearly complete, with only path-resolution and failure-mode behavior unstated.

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 coverage is 0% for the single parameter, so the description must compensate. It defines 'path' as the 'folder to scan', which adds real meaning beyond the bare string, but leaves open whether the scan is recursive, how relative paths resolve, and what the default '.' covers.

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?

The description names a specific verb and artifact: 'Propose a safe .env.example as text', scoped to 'one section per env root'. That is clearly distinct from validate_env or compare_env, but it never explicitly names a sibling or states the boundary, so it stops short of a 5.

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?

Usage is only implied: an agent can infer this is the tool for producing a starter example file, and the 'nothing is written to disk; paste or save the text yourself' line hints at the workflow. There is no explicit when-to-use/when-not guidance and no reference to the sibling tools that cover the other .env tasks.

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