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kernl

kernl

by fastslack
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TypeScript
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kernel_agents_set_skills

Attach or replace the procedural skills an agent uses by assigning installed skill slugs; pass an empty array to detach all skills.

Instructions

Attach (or replace) the procedural skills loaded by an agent. Each slug must reference an installed extension with type='skill'. Pass an empty array to detach all.

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": {
      "agent_id": "<agent_id>",
      "skills": "<skills>"
    },
    "name": "kernel_agents_set_skills"
  }
}

Input Schema

NameRequiredDescriptionDefault
skillsYesArray of skill slugs
agent_idYesTarget agent id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full behavioral burden. It does disclose the two most important traits for a mutation tool: the set is replaced wholesale, and an empty array detaches everything. However, it omits what happens with an invalid or non-skill slug (hard error vs. skipped), whether the write is atomic, and whether running agents pick up the change immediately.

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 short sentences, no filler, with the mutation/replacement semantics front-loaded before the validation constraint and the detach edge case. Every sentence carries distinct information.

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 two-parameter tool with fully documented schema and no output schema, this is nearly sufficient: purpose, input constraint, and the destructive edge case are all covered. The remaining gap is error/failure behavior on bad slugs, which matters for a replace-all mutation but is a minor omission at this complexity.

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, but the description earns above baseline by adding meaning the schema lacks: skills entries must be slugs of installed extensions with type='skill', and an empty array is a valid sentinel meaning detach all. That materially changes how an agent should construct the skills array.

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?

States a specific verb pair ('Attach (or replace)') and a specific resource ('procedural skills loaded by an agent'), which distinguishes it from the read-side sibling kernel_agents_get_skills by implication. It never names that sibling, so the differentiation is inferred rather than explicit.

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?

Gives one concrete usage rule (empty array detaches all) and a precondition (each slug must reference an installed extension with type='skill'), but says nothing about when to reach for this versus updating an agent's other configuration surfaces (flows, decision policy, learnings). Usage is implied by the verb, not spelled out.

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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