Skip to main content
Glama

prufa_run_gremlin

Impersonate a difficult user to stress-test a real browser flow and automatically detect broken functionality, console errors, and accessibility issues.

Instructions

Run a gremlin chaos-QA session on a URL: an agent imitates a difficult user (no script) while plain-code detectors verify what breaks. Use to stress-test a real flow beyond the deterministic audit. Mutations are DRY-RUN unless the host is authorized via prufa_authorize_domain; payments are NEVER executed. Optional credentials (a real, non-payment login write) require a signed-in workspace AND mutation authorization for the host. Step budget depends on plan (free teaser 8, Starter 20, Pro 40, Team 60) — call prufa_get_usage for the cap. wait=true (default) blocks until the run completes (can take ~5 min) and returns the report; wait=false returns the queued state with run_id. [Pro]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
waitNo
personaNoWhich difficult-user persona to play.
directionNoFreeform nudge for what the gremlin should try.
credentialsNo
idempotency_keyNoOptional. Replays of the same key within 24h return the original response without re-executing — pass one to make retries safe. Omitted: a fresh key is generated, so each call executes.
Behavior4/5

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

With no annotations, the description carries full burden and reveals key behaviors: dry-run unless authorized, no payments, credential requirements, wait behavior, plan-dependent step budget. Lacks error/timeout details but still strong.

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?

Packed with information but slightly lengthy. Front-loaded with core purpose, then conditions and details. Could be more concise but well-structured with clear sections.

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 no output schema and a complex tool, the description covers purpose, usage, behavior, dependencies, parameters, and plan limits. Defines return format for wait=true/false. Very complete.

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 50%; description adds context for url, wait, credentials, and idempotency_key beyond schema. Provides usage guidance for wait and idempotency, and prerequisite for credentials.

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 it runs a gremlin chaos-QA session on a URL, imitating a difficult user with plain-code detectors. It distinguishes itself from sibling tools like prufa_run_audit and prufa_run_flow.

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?

Explicitly mentions when to use (stress-test real flows beyond deterministic audit), when not to use (mutations only dry-run unless authorized), and alternatives (prufa_authorize_domain, prufa_get_usage for budget).

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/prufa-dev/prufa-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server