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neuron_evaluate_js

Evaluates JavaScript expressions inside a specific Chrome tab and returns the result. Use this to inspect or modify page state directly from your MCP client.

Instructions

Run JavaScript in page context and return the result

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tabIdYesChrome tab ID
expressionYesJavaScript expression to evaluate

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.4.1

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention potential side effects of running JavaScript, how returned values are serialized, how errors are handled, whether promises are awaited, or any security implications. These are significant unknowns for a page-context JS execution tool.

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 a single, clear sentence with no filler. It front-loads the action and outcome and is appropriately sized for a relatively simple tool.

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

Completeness3/5

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

With only two self-describing parameters and no output schema, the description is minimally viable. However, it omits important behavioral context for JavaScript execution: result serialization behavior, error propagation, async handling, and side-effect warnings. These gaps matter for an agent invoking arbitrary page code.

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 100%, and both parameters already have descriptions. The tool description adds little beyond the schema, only reinforcing that the expression is JavaScript running in page context. Baseline 3 is appropriate because the schema already handles parameter documentation.

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 action ('Run JavaScript'), the context ('in page context'), and the expected outcome ('return the result'). This clearly distinguishes it from sibling tools like neuron_query_dom and neuron_find_elements, though it does not explicitly name them.

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

Usage Guidelines2/5

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

The description gives no explicit guidance on when to use this tool versus alternatives. It implies usage for executing arbitrary JavaScript, but does not mention exclusions, preferred scenarios, or why it should be chosen over the many DOM/traffic/session siblings.

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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