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Launch a web-agent browser mission

neuron_webagent_run

Queue a browser mission for the user's Neuron extension to run — mine content into a Collection or prospects into the lead pool. Returns a command id; the extension picks it up on its next poll (so the browser must be open, signed in, and remote-control enabled in the extension). Watch it with neuron_webagent_list_runs / neuron_webagent_get_run and stop it with neuron_webagent_kill.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hopNoactive posture: multi-hop navigation from seeds.
urlNoOptional page to open the mission on (else the platform home / active tab).
capsNoStop conditions.
sinkNoWhere output goes (defaults to match the mission).
seedsNoactive posture: starting URLs (hashtag/search/profile pages) to crawl from.
pacingNoSpeed/rate (default normal).
missionYescontent = capture posts into a Collection; leads = capture prospects into the lead pool.
postureNoHow much it interacts (default read-light; 'active' enables hop + cinematic).
leadTagsNoleads mission: tags to attach to captured leads.
platformYesig=Instagram, x=X/Twitter, tk=TikTok, li=LinkedIn, fb=Facebook.
cinematicNoactive posture: cinematic reel/video capture.
collectionNameNocontent mission: the Collection to fill (created if new).

Schema Changelog

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

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Beyond the annotations, the description reveals that this is an asynchronous, queued operation rather than a synchronous launch, and that it depends on the extension being active and connected. It also discloses that the return value is a command id, which is useful because no output schema is present.

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?

Two sentences front-load the core action and return behavior, then add the prerequisite, monitoring, and stopping guidance without redundancy. Every phrase contributes useful information.

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?

For a complex 12-parameter tool with no output schema, the description covers the essential launch-monitor-stop workflow, the async pickup model, and the environment prerequisites. Detailed parameter semantics are appropriately left to the richly described schema, though the description could improve by acknowledging the related open_launcher and stop siblings.

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 description coverage is 100%, so the input schema already documents each parameter. The description adds a high-level mapping of mission types to outputs, but this largely restates what the mission and sink enum descriptions already say, so it does not exceed the schema baseline.

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 states a specific action — queue a browser mission for the user's Neuron extension — and names the two possible outcomes: mining content into a Collection or prospects into the lead pool. It also differentiates itself from sibling monitoring and control tools by naming neuron_webagent_list_runs, neuron_webagent_get_run, and neuron_webagent_kill as follow-up operations.

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?

It gives clear operational context: the mission is queued and picked up on the next extension poll, so the browser must be open, signed in, and remote-control enabled. It names monitoring and stopping alternatives, though it does not explicitly state when a sibling such as neuron_webagent_stop or neuron_webagent_open_launcher should be preferred.

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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TDQS

B3.4/5.0
Disambiguation3/5

Most tools are clearly separated by resource type, but there is meaningful overlap in messaging entry points (send_message, send_whatsapp, compose_message, bot_api_send) and contact ingestion/sync tools (import_contacts, populate_contacts, sync_whatsapp_contacts). The descriptions help disambiguate, but with 309 tools an agent will frequently need to read closely to pick the right one.

Naming Consistency4/5

The overwhelming majority of tools follow a consistent verb_noun snake_case pattern: create_*, get_*, list_*, update_*, delete_*. Minor deviations like sales_stats, lead_stats, wallet_balance, and whoami break the pattern slightly, but overall naming is highly predictable.

Tool Count1/5

309 tools is an extreme count for any MCP server, even a broad platform. This creates significant cognitive load and navigation overhead for agents, and far exceeds the well-scoped 3-15 tool range where coherence is strongest.

Completeness4/5

The tool surface is remarkably comprehensive across bots, contacts, campaigns, flows, knowledge bases, personas, marketplace, wallet, and products. Minor gaps exist — lead sources lack update/delete tools, and there is no single get_task or get_webhook alongside their list/update/delete counterparts — but these are workable gaps rather than dead ends.

Resources