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SassyMCP

Official
by sassyconsultingllc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

sassy_env_list

Read-onlyIdempotent

List environment variables of the MCP server process, sorted by name, with optional case-insensitive filter. Sensitive values are masked. Use it to discover available variables before retrieving or setting them.

Instructions

Read-only. Lists environment variables of the SassyMCP server process, sorted by name, with their count. filter_str (string, default empty) limits results to variable names containing that case-insensitive substring. Values that look sensitive (names containing token, key, secret, password, api, or credential) are masked to the first 4 and last 4 characters (or **** if short); other values are truncated at 200 characters. Use it to discover available variables before calling sassy_env_get, and use sassy_env_set to change one.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filter_strNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv1.15.1
    • addedOutput schema / additionalProperties
      Added value: +true
    • removedOutput schema / properties
      Removed value: -{
-  "result": {
-    "title": "Result",
-    "type": "string"
-  }
-}
    • removedOutput schema / required
      Removed value: -[
-  "result"
-]
    • changedOutput schema / title
      Previous value: -"sassy_env_listOutput"New value: +"sassy_env_listDictOutput"
  2. First observedv0.1.0

TDQS

A5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint=false, idempotentHint, and destructiveHint=false. The description adds substantial behavioral context beyond that: the output is sorted with a count, sensitive values are masked with a specific rule, non-sensitive values are truncated at 200 characters, and filtering is case-insensitive. This fully discloses behavior without contradicting 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?

Every sentence earns its place: read-only marker, output format, filter behavior, masking rule, truncation rule, and usage routing. The structure is logical and efficient with no redundant or filler content.

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 a single optional parameter and an output schema (which handles return-shape documentation), the description covers all necessary call-time knowledge: what is listed, ordering, counting, masking, truncation, and how to use the filter. Nothing essential is missing for this tool's complexity.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must carry the full burden for the filter_str parameter. It does so by specifying the type, default, and precise semantics: limits results to variable names containing the case-insensitive substring. This is complete and adds meaning the schema lacks.

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 ('Lists') and resource ('environment variables of the SassyMCP server process'), along with formatting details (sorted by name, with count). It explicitly differentiates from sibling tools by naming sassy_env_get and sassy_env_set as related but distinct actions, so an agent can tell them apart.

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?

Description explicitly says to use this tool to discover available variables before calling sassy_env_get, and directs that changes go through sassy_env_set. This provides clear when-to-use guidance and routes to the correct alternatives without requiring the agent to infer from names alone.

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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