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jevnav

by dtduc-git
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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goal

Destructive

Drive browser automation toward a specified goal with an agent that chooses each step, accepts context variables, and verifies completion via a visible selector, returning the outcome and cost.

Instructions

Drive the browser towards a goal: Jev decides every step, jevnav acts.

    ``context_json`` is a JSON object of values the goal may need, e.g.
    {"email": "a@b.c", "password": "${PW}"}. ``success`` is a selector that
    must be visible when the goal is done: pass it and the outcome comes
    back verified or the run is reported as unverified. Returns the outcome
    (done, stuck, review, ...), the steps taken, cost and the verification.
    Risky steps stop the loop and come back unexecuted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalYes
successNo
max_stepsNo
context_jsonNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, readOnlyHint=false, openWorldHint=true, idempotentHint=false. The description adds valuable context: risky steps stop the loop and come back unexecuted, success verification is built-in, and the outcome includes done/stuck/review states. This goes beyond the annotations and helps the agent understand the tool's safety and control flow.

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 description is compact and front-loaded with the core purpose. The parameter explanations are integrated naturally. It's slightly dense with the 'Jev decides, jevnav acts' phrasing, which may be jargon, but it's not bloated. Every sentence adds value.

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?

The tool is complex (autonomous loop, verification, risky-step handling) and has an output schema, so the description doesn't need to detail return values. It covers the main behavioral aspects: goal-driven execution, success verification, risky-step stopping, and context injection. It could mention max_steps behavior or what 'review' means, but overall it's complete enough for an agent to call it correctly.

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 description coverage is 0%, so the description must compensate. It explains context_json (JSON object of values the goal may need, with an example) and success (selector that must be visible when done, with verification behavior). It doesn't explain goal, max_steps, or the exact format of context_json beyond the example, but the key parameters are covered. Given the low schema coverage, this is a strong effort.

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 states a specific verb ('Drive the browser towards a goal') and resource, and explains the high-level behavior: Jev decides, jevnav acts. It distinguishes itself from siblings like goto, browse, and fill_form by being an autonomous goal-driven loop rather than a single action. However, it doesn't explicitly name a sibling alternative, so it's clear but not fully differentiated.

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 this tool: when you have a goal and want the agent to decide steps. It also implies when not to use it: for direct, single actions like goto or fill_form. It doesn't explicitly state exclusions or alternatives, but the context is clear enough for an agent to select it appropriately.

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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