Skip to main content
Glama

skills_list

List available food chemistry and recipe optimization skills to help AI agents discover supported nutrition, macro, and recipe analysis capabilities.

Instructions

List available food chemistry and recipe optimization skills.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing beyond the verb. Read-only/non-destructive behavior is only weakly implied by "List," and nothing is said about whether skills are filtered, paged, or scope-limited.

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?

A single, front-loaded sentence with zero filler that states the action and the domain in one pass.

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 zero-parameter listing tool with an output schema, the description covers what an agent needs to invoke it correctly. The remaining gap is that it does not connect the listed skills to the sibling skill_read, which would complete the workflow picture.

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?

The tool takes zero parameters, so there is nothing to document; the baseline of 4 applies. The description adds no parameter detail because none is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a clear verb ("List") and resource ("skills") and scopes it to "food chemistry and recipe optimization," so an agent knows what it returns. It stops short of distinguishing itself from the sibling skill_read, which is the natural follow-up tool, so it is not a 5.

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

Usage Guidelines3/5

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

"List available ... skills" implies a discovery step that logically precedes skill_read, so usage is reasonably inferable. However, there is no explicit when/when-not guidance and no mention of the skill_read alternative for acting on a listed skill.

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