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Prufa

Prufa

Official
by prufa-dev
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Python
Remote

prufa_authorize_domain

Authorize real (non-payment) mutations on a host, enabling login and write operations to stop being dry-run. Set allow_mutation=false to revoke authorization.

Instructions

Authorize REAL (non-payment) mutations for the gremlin on a host you own or a staging host — logging in and writing on that host stop being dry-run. Set allow_mutation=false to revoke. This is the gremlin mutation opt-in, NOT the discovery DNS-domain verification (a different system). host is a bare hostname (e.g. staging.acme.com). [Pro]

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": {
      "host": "<host>"
    },
    "name": "prufa_authorize_domain"
  }
}

Input Schema

NameRequiredDescriptionDefault
hostYesBare hostname (no scheme/path), e.g. staging.acme.com.
noteNoOptional operator note.
allow_mutationNotrue authorizes real mutations; false revokes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.3

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It discloses that authorizing makes logging in and writing on the host no longer dry-run, and that revoking stops real mutations. It also notes it's the gremlin mutation opt-in, not discovery verification. Side effects are implied but not exhaustive (e.g., no mention of permissions or rate limits).

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?

The description is concise: a few sentences with front-loaded purpose, no redundant words. It efficiently conveys the tool's intent, usage, and caveats.

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?

No output schema exists, but the description explains behavioral outcomes (authorize/revoke) and differentiates from discovery verification. It mentions ownership requirements and host format. Adequate for an agent to decide when to use this tool.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value by explaining host is a bare hostname with an example, and clarifies allow_mutation's default and effect. Note is optionally mentioned but no extra semantics.

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?

The description clearly states the tool authorizes real mutations for the gremlin on a host, distinguishes it from discovery DNS-domain verification, and specifies it is not related to payments. The verb 'authorize' and resource 'domain' with mutation context are specific and differentiated from siblings.

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

Usage Guidelines4/5

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

The description explains when to use (to authorize mutations), how to revoke (set allow_mutation=false), and what constitutes a valid host (bare hostname, host you own or staging). It explicitly differentiates from discovery verification. No explicit 'when not to use' is given, but context is clear.

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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