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kernl

by fastslack
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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kernel_office_pack_import

Import a knowledge pack into an office for review: lessons are matched to agents, compared with existing knowledge, and staged until accepted through review.

Instructions

Bring a knowledge pack (the JSON or Markdown that kernel_office_pack_export makes) into an office, for review. Lessons are matched to the office's agents by name (or by role when one agent has it; agent_map overrides), compared with what they already know, and staged — none reaches an agent until accepted with kernel_office_pack_review. Accepted lessons start at confidence 0.6 at most.

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": {
      "office": "<office>",
      "pack": "<pack>"
    },
    "name": "kernel_office_pack_import"
  }
}

Input Schema

NameRequiredDescriptionDefault
packYesThe pack's content.
officeYesOffice id or name.
sourceNoWhere it came from, for the record (a repo, a person).
agent_mapNoPack agent name → this office's agent id or name.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the matching algorithm (name first, role when unique, agent_map overrides), that lessons are compared against existing knowledge, that import is non-destructive staging, and the 0.6 confidence ceiling on accepted lessons. Gaps remain on re-import/idempotency and what happens on conflicting or duplicate lessons.

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 tight sentences, front-loaded with the core action, then the matching/staging mechanics, then the acceptance outcome. The parenthetical identifying the export counterpart is the only optional clause and it earns its place by pinning the input format.

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?

An output schema exists, so return values need no explanation, and the description covers the consequential behaviors (matching, staging, review gate, confidence cap) for a 4-parameter import. It stops short of describing failure modes or repeated-import behavior for a workflow that clearly can be run more than once.

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 coverage is 100%, so the baseline is 3, and the description adds little per-parameter detail beyond explaining that agent_map overrides the default name/role matching. That override note is genuine added meaning, but pack/source/office are left entirely to the schema.

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 ('Bring a knowledge pack ... into an office') and anchors the input format by naming kernel_office_pack_export as its producer. The downstream staging/review relationship to kernel_office_pack_review makes it distinguishable from both siblings without opening a 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 operational context: the pack is imported 'for review' and nothing reaches an agent until accepted with kernel_office_pack_review, which explicitly names the follow-up tool. It does not contrast with kernel_marketplace_import, the other import-shaped sibling, so the when-not guidance is incomplete.

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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