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kernl

kernl

by fastslack
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TypeScript
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kernel_brain_feedback

Record usage signals for recalled items to teach memory ranking: open/correct promote relevance, ignore demotes, adapting future recalls to your behavior.

Instructions

Record a usage signal for a recalled item to teach the brain. open/correct promote it, ignore demotes it. This is the autoaprendizaje loop — future recalls rank adapted to your behaviour.

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": {
      "item_id": "<item_id>",
      "signal": "<signal>"
    },
    "name": "kernel_brain_feedback"
  }
}

Input Schema

NameRequiredDescriptionDefault
signalYesUsage signal driving the weight nudge.
item_idYes

Output Schema

NameRequiredDescriptionDefault
weightYes
item_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations supplied, the description carries the full burden and does disclose the core behavior: this mutates ranking weights, promoting on `open`/`correct` and demoting on `ignore`. It omits whether the item must exist beforehand, whether feedback is reversible or cumulative, and what happens to `co_open`, leaving real gaps for a mutation tool.

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, front-loaded with what the tool does, then the signal semantics, then the rationale. Nothing is padded, and the promote/demote mapping is easy to scan.

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?

An output schema exists, so return values need no explanation, and the promotion/demotion model is covered. Still missing is where `item_id` comes from (presumably a prior recall), what `co_open` means, and any note on repeat signals - meaningful omissions for a two-parameter mutation tool.

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 only 50%, and the description does compensate partially by explaining what `open`, `correct` and `ignore` do to the ranking. However `co_open` - one of four enum values - is never explained, and `item_id` is left with no description in either the schema or the description.

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 states a specific verb and resource - recording a usage signal for a recalled item - and names the effect (teaching the brain, adjusting future recall ranking). That is enough to separate it from siblings like kernel_brain_recall or kernel_agents_feedback 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 Guidelines3/5

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

Usage is implied rather than stated: the mention of 'a recalled item' and 'future recalls rank adapted' suggests calling this after a recall to shape later results. There is no explicit when-to-use trigger, no when-not-to-use, and no named alternative tool for comparison.

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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