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Glama
aibtcdev
by aibtcdev

inbox_auto_reply_configure

Configure auto-reply behavior for inbox messages by setting the agent's system prompt, model, enablement, and daily/per-reply sat spending caps.

Instructions

Configure inbox auto-reply (stored in ~/.aibtc/config.json). Call with no arguments to see the current settings. A systemPrompt (the agent's voice / personality / what it can help with) is required before auto-reply can be enabled. The model must be live on inference.aibtc.com; it is checked against the catalog when set. dailyCapSats caps sats spent on reply inference per UTC day, on top of the wallet-wide spending limit. maxSatsPerReply is the most one reply may cost; a higher quote stops the run unpaid.

Tip: call earning_opportunities to see how to put your assets to work.

Input Schema

NameRequiredDescriptionDefault
modelNoInference marketplace model id (see GET https://inference.aibtc.com/v1/models). Default meta-llama/Llama-3.1-8B-Instruct.
enabledNoAllow inbox_auto_reply to post replies. Dry runs work while disabled.
dailyCapSatsNoMost sats spent on reply inference per UTC day. Default 1000.
systemPromptNoSystem prompt for reply generation: who the agent is, its tone, what it offers, what it won't do.
maxSatsPerReplyNoMost sats paid for one reply. Default 10.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.77.1

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided the description carries the full burden, and it delivers meaningful behavior: the config file location, live model validation against the inference catalog, and spend semantics (dailyCapSats stacks on the wallet-wide limit, maxSatsPerReply stops a run unpaid on a higher quote). It doesn't state whether changes take effect immediately or how partial updates behave, so not a 5.

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 read-mode instruction and the systemPrompt prerequisite are front-loaded, and most sentences earn their place. The appended earning_opportunities tip is off-topic noise and the run-on dailyCapSats/maxSatsPerReply sentence could be split.

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?

Five optional params, no annotations and no output schema, so the description must cover safety and prerequisites — it does (validation, spend caps, enable gate). Only the read-path return shape and the effect of omitting fields are left unspecified.

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 100% so baseline is 3, but the description adds real meaning beyond it: systemPrompt is framed as the agent's voice/personality, dailyCapSats is explicitly 'on top of the wallet-wide spending limit', and maxSatsPerReply is tied to the unpaid-stop behavior.

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?

States a specific verb and resource ('Configure inbox auto-reply') plus where the config lives, and implicitly distinguishes from the sibling 'inbox_auto_reply' that actually posts replies. An agent can tell which of the two to reach for.

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?

Gives useful routing cues: call with no arguments to read current settings, and systemPrompt must exist before enabling. It does not explicitly name the sibling tool or state exclusions, and the closing 'earning_opportunities' tip is unrelated to this tool's use.

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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