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agentskills-mcp

agentskills-mcp

by janacibron
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Get Skill Asset

get_skill_asset

Read a specific file from a skill's assets directory by skill ID and filename to retrieve supporting resources for agent tasks.

Instructions

Read a specific asset file from a skill's assets/ directory.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "skill_id": "<skill_id>",
      "name": "<name>"
    },
    "name": "get_skill_asset"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYesFilename within assets/.
skill_idYesDirectory name of the skill.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden. "Read" implies a non-mutating operation, but nothing is said about what happens on a missing file, whether binary vs. text assets are returned differently, or any size or permission constraints.

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 sentence with zero filler, and the resource scope is front-loaded where an agent will read it first. Nothing is repeated or padded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter read tool this covers the core purpose, but with no output schema the description should indicate what is returned (raw text, binary payload, or a path). That return-value ambiguity is the main remaining gap.

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

Parameters3/5

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

Schema description coverage is 100%, with both skill_id and name documented inline, so the baseline is 3. The description adds only the framing that name resolves inside assets/, which the schema already states.

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 pairs a specific verb ("Read") with a precise resource (an asset file inside a skill's assets/ directory), which separates it from get_skill_reference, get_skill_script, and get_skill_body by resource type. It stops short of naming those siblings explicitly, so the differentiation is implied rather than stated.

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?

Usage is only inferable: an agent can deduce this is the fetch step after list_skill_assets, but the description never says so and gives no when-not conditions. There is no mention of what to do when the name is unknown or when the asset does not exist.

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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