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Vilix AI

message_agents

Post a message to the user's OWN running agents. Vilix delivers it inside the inbox field of every matching Vilix read call (get_context, searches, recent_messages, get_project, get_skill, list tools) those agents make — a push channel that rides their next memory read, from any connected client including a phone.

body (required) — the message, markdown, max 2000 chars. urgency — "normal" (default: delivered once per chat, then done) or "urgent" (redelivered on EVERY read in every chat until the receiving agent calls ack_message, or the message expires). scope_type — who should receive it: "global" (default, all of the user's agents), "project" / "task" (only chats whose context touches that project — pass the project/task id you OWN in scope_value), or "source" (only agents running on one platform label, e.g. "Claude Code" — pass the label in scope_value). ttl_hours — expiry, default 24, max 168 (7 days). Max 20 unexpired messages per user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
urgencyNo
ttl_hoursNo
scope_typeNo
scope_valueNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
noticeNo
messageNo
upgrade_urlNo
agent_messageNo
advisory_nonceNo
server_advisoryNo

Schema Changelog

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

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations indicate only non-read non-destructive behavior (readOnlyHint=false), but the description goes well beyond that: it discloses redelivery semantics for 'urgent', the default delivery once per chat, expiry range, global unexpired limit, and that messages ride the next matching read call. This is rich behavioral context that an agent needs to call the tool correctly without side-effect surprises.

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 packed with necessary detail and is organized from the core action to delivery mechanism to parameter specs, all front-loaded with the most important purpose. Each sentence earns its place. Minor deduction: it reads slightly dense and could benefit from very light formatting separation, but this is still strong and efficient.

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?

Despite having 5 parameters and no schema-level descriptions, the description covers every parameter's meaning, defaults, and constraints, and explains the delivery side-effect well. It doesn't explicitly describe return values, but an output schema exists. It also doesn't explicitly state the behavior after ack_message for non-urgent messages, but that's a minor edge case. Overall, highly complete for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description bears full responsibility for parameter semantics — and it fulfills it. It explains `body`, `urgency`, `scope_type` (with its sub-values global/project/task/source and what to pass in `scope_value`), and `ttl_hours` defaults and bounds. It essentially compensates for the empty schema descriptions, which earns a 5.

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 begins with a specific verb-resource pair ('Post a message to the user's OWN running agents') and clearly distinguishes this tool from siblings like ack_message and save_turn. The subsequent details about delivery via Vilix read calls and its push-channel behavior further pin down exactly what this tool accomplishes, leaving no ambiguity about its role.

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 the mechanism (delivered in the `inbox` field of matching read calls) and gives concrete defaults, maxes, and scope options, giving an agent enough context to decide when to use it. It does not explicitly name sibling alternatives or state when NOT to use it, so it stops short of a 5, but the delivery mechanics and constraints effectively imply appropriate usage.

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

A3.8/5.0
Disambiguation4/5

Most tools map cleanly to distinct resource+action pairs: projects, tasks, skills, user rules, memory, and messaging are all clearly separated. The main ambiguity is update_task versus update_task_state, since update_task can also change state and plan_status, though the descriptions do point to the narrow intended use.

Naming Consistency4/5

The naming is largely consistent verb_noun snake_case: create_project, update_skill, delete_task, list_projects, get_context, save_turn. Minor deviations include recent_messages lacking a verb, remove_user_rule versus delete_* style, and singular user_rule in mutations versus plural user_rules in listing.

Tool Count2/5

With 27 tools, the server is over the typical well-scoped MCP range, even though it covers several domains. Some consolidation is possible, such as folding update_task_state into update_task and reducing the overlapping retrieval/search tools.

Completeness4/5

The tool set provides strong lifecycle coverage for projects, tasks, skills, and user rules, plus memory retrieval, agent messaging, and onboarding help. Minor gaps exist, like no standalone get_task or list_tasks and no explicit inbox listing, but get_project and get_context largely cover those needs.

Resources