Skip to main content
Glama
SVerITG

Metis

by SVerITG
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

propose_skill_improvement

Propose updates to an agent's skill file for human review. Submit proposed content and rationale to queue a change that requires approval.

Instructions

An agent proposes a change to its own skill file.

The proposal is queued for human review. The skill file is NOT modified
until the user calls approve_proposal().

Args:
    agent_slug: The agent's slug (e.g. 'librarian', 'writing-partner')
    proposed_content: The full proposed replacement content of the skill file
    rationale: Why this change is being proposed (1–3 sentences)

Returns:
    Confirmation with the proposal ID for the user to review

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_slugYes
proposed_contentYes
rationaleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.5/5.0
Behavior4/5

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

No annotations provided; description carries the burden. It discloses that the skill file is not modified until approval, but could add more details on immutability or permissions.

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?

The description is concise with no extraneous content, structured into purpose, behavior, args, and returns.

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?

Given the simple tool and absence of output schema details in the description, the return type is vaguely mentioned. However, it covers key aspects; slight improvement could detail the confirmation structure.

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 coverage is 0%, but the description fully compensates with clear parameter explanations for `agent_slug`, `proposed_content`, and `rationale`, adding types and examples.

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 clearly states the tool's purpose: 'An agent proposes a change to its own skill file.' It distinguishes from siblings like `approve_proposal` by noting the proposal is queued and the file is not modified until approval.

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 when to use the tool (to propose a change requiring human review) and what happens next, but does not explicitly contrast with other proposal tools like `draft_self_improvement_proposal_tool`.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/SVerITG/Metis'

If you have feedback or need assistance with the MCP directory API, please join our Discord server