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read_skill

Read one skill from a vault to retrieve its name, description, and full instructions, so you can follow the right procedure after selecting it from a skill list.

Instructions

Read one skill from a skill vault: its name, description and full instructions. Use this after list_skills, once you know which procedure fits the task, and follow the instructions it returns.

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": {
      "vault_name": "<vault_name>",
      "skill_name": "<skill_name>"
    },
    "name": "read_skill"
  }
}

Input Schema

NameRequiredDescriptionDefault
skill_nameYes
vault_nameYes

Output Schema

NameRequiredDescriptionDefault
skillYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.9.1

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the disclosure burden. It makes the read-only nature clear through "Read" and describes the payload shape (name, description, full instructions), and the presence of an output schema reduces the need to enumerate return fields. It says nothing about permission requirements, lookup failure behavior, or whether instructions are versioned/stale.

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?

Two sentences, front-loaded with the core action and payload, followed by the usage sequence. No redundant restatement of the title or filler wording.

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?

The output schema covers return values and the description covers purpose plus workflow position, so the main gaps are the two required parameters, which have zero schema documentation and no description-level explanation, and the absence of any failure-mode information. For a simple two-parameter read tool with an output schema, that is adequate but incomplete.

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

Parameters2/5

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

Schema description coverage is 0% and neither parameter has any documentation in the schema. The description only obliquely implies what vault_name and skill_name mean ("from a skill vault", "its name") and adds no format, casing, or identifier-convention detail, so it does not compensate for the coverage gap.

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 ("Read one skill from a skill vault") and enumerates what is returned: name, description, and full instructions. That scope statement is enough to distinguish it from list_skills (many) and write_skill (mutation) without opening either 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 concrete sequencing guidance: call it after list_skills, once the procedure matching the task is known, then follow the returned instructions. It names the predecessor tool and the selection condition, but offers no explicit exclusions or edge cases (e.g., unknown skill name).

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