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Vilix AI

create_skill

Save a reusable Agent Skill — a how-to procedure the user wants followed for a recurring task (e.g. "check active users"), so any AI does it the right way without re-explaining. Skills-first default: when you work out a non-trivial procedure that went well, OFFER to save it here for next time — suggest and confirm first (don't save silently or for trivial one-offs), and call list_skills first so you don't create a duplicate. name is a short trigger label; description is ONE line on when to use it (this is what every agent sees in the index); body is the full step-by-step procedure in markdown (loaded on demand via get_skill). Omit project_id for a GLOBAL skill (available in every chat) or pass a project id to scope it to that project. Per-plan skill cap applies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNo
nameYes
enabledNo
project_idNo
descriptionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
inboxNo
skillNo
messageNo
instructionNo
upgrade_urlNo

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already mark this as a non-read, non-idempotent write, and the description adds valuable behavior beyond that: suggest and confirm before saving, don't create duplicates by checking list_skills, and the per-plan skill cap. It doesn't cover auth or rate limits, but those are not strongly implied by the annotations.

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 dense but organized: purpose first, then usage policy, then parameter semantics, then scoping. It is longer than strictly necessary, but each sentence adds decision-relevant information rather than padding.

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 five-parameter creation tool with no schema descriptions, the description covers purpose, when to use it, how to avoid duplication, parameter meaning, scoping, and plan limits. The only material omission is the enabled parameter, and the existence of an output schema means return-value explanation is not required.

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?

With 0% schema description coverage, the description carries the full explanatory burden and does so for name, description, body, and project_id, including the indexing and lazy-loading behavior. The only gap is the 'enabled' parameter, whose meaning is left entirely to inference.

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?

Opens with a specific verb and resource ('Save a reusable Agent Skill') and defines it as a how-to procedure for a recurring task, with a concrete example. It also orients the agent against sibling tools by referencing list_skills for duplicates and get_skill for body loading.

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

Usage Guidelines5/5

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

The description gives explicit trigger conditions: offer to save after a non-trivial procedure, confirm first, avoid silent or trivial saves, and call list_skills before creating. It also explains global vs project scoping, which is exactly the decision an agent needs to make before invoking.

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