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neuron_trigger_post

Claims and executes the next pending post task from the Neuron backend, using Chrome's logged-in session to post to Instagram.

Instructions

Trigger the IG post runner to claim and execute the next pending post task from the Neuron backend. Posts to Instagram using the logged-in session in Chrome.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv0.4.1

TDQS

A4.1/5.0
Behavior3/5

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

There are no annotations, so the description must carry the behavioral burden. It does disclose the key side effect: this tool will actually post to Instagram using the logged-in session. However, it does not mention whether the action is reversible, whether it waits for completion, failure behavior when no task is pending, or that it is a side-effectful public action.

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, both meaningful: the first defines the trigger and the backend source, the second clarifies the actual posting side effect. No filler or unnecessary detail.

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?

For an externally visible action with no annotations and no output schema, the description is functionally adequate but not rich. It tells an agent what happens and where, but it omits important operational context such as whether the call returns after triggering or after execution, what failure modes look like, and whether this permanently publishes content.

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?

The tool has zero parameters, so parameter semantics are vacuous. The baseline for a no-parameter tool is 4, and there is no schema information the description needs to supplement.

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?

Description clearly identifies a specific action (trigger/claim/execute), a resource (IG post runner, pending post task), and the effect (posts to Instagram via the logged-in Chrome session). It is easy to distinguish from the many sibling tools because it names the exact pipeline and outcome.

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 gives clear context: call this tool when you want the Neuron post runner to pick up and execute the next pending Instagram post. It does not explicitly list when not to use it or name alternative tools, but no obvious sibling performs this same task, so the context is sufficiently 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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