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Submit Skill

submit_skill

Submit a skill to ecomdly for review (needs sign-in). Creates it under your account — or a new version if you already own one with this name — runs the automated checks and the AI safety scan, and queues it for a human reviewer. Nothing is published by this tool; you get the check results back. The body must be a complete Markdown skill with a title and a "## License" section (MIT recommended).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesFull Markdown: # title, when to use, rules, output format, ## License
nameYeskebab-case skill name, unique within your account
noteNoRelease note when submitting a new version of an existing skill.
categoryNoCategory name; required for a new skill.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and does so well: auth requirement (sign-in), side effect semantics (creates under your account or a new version if the name is already owned), downstream processing (automated checks + AI safety scan + human review queue), and the key negative guarantee that nothing is published and the check results are returned.

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?

Three sentences, front-loaded with the action and audience, then outcomes, then the body requirement. No filler; each sentence adds a distinct, load-bearing fact.

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 4-param mutation tool with no annotations and no output schema, this covers authentication, side effects, and processing pipeline thoroughly. The one remaining gap is the shape of the returned check results ('you get the check results back' without describing format or failure cases), which the agent may need.

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 the baseline is 3; the description adds value by imposing a body contract beyond the schema's terse hint — a complete Markdown skill with a title and a '## License' section, with MIT recommended. It does not elaborate on the note or category params, which the schema already covers.

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 ('Submit a skill to ecomdly for review') and immediately describes the full lifecycle: create-or-new-version, automated checks, AI safety scan, human review queue. An agent can distinguish this from install_skill/get_skill/search_skills without opening any schema.

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 clear context: requires sign-in, operates on your account, and explicitly states that nothing is published so the agent knows this is not a publish path. It does not name sibling alternatives (e.g. install_skill or design_publish) for related goals, so it falls just short of the explicit when/when-not routing bar.

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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