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aiworkhub_manager_skill_mine

Read-only

Clusters stored rejection instructions and adjudicated invariants by asserted rule, then returns read-only, evidence-backed gated skill proposals for families recurring across cards and files.

Instructions

MANAGER READ: mine the correction record into gated skill PROPOSALS.

Clusters every stored rejection instruction and adjudicated invariant by the RULE it asserts -- instance vocabulary (paths, identifiers, ids, digits) is deleted before anything is compared -- then promotes only families that recurred across at least min_cards distinct cards in min_files distinct files. Each candidate carries the exact card ids and request ids where the rule was violated, plus a proposal draft whose closed-vocabulary selection dimensions are left blank for the manager to fill in.

Read-only. It produces proposals, never activations: the returned draft reaches the store only if a manager proposes it through the skill-proposal step, and activation remains gated on evidence from two distinct actor identities.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "aiworkhub_manager_skill_mine"
  }
}

Input Schema

NameRequiredDescriptionDefault
min_cardsNoMinimum distinct cards a family must recur across to become a candidate; default 3.
min_filesNoMinimum distinct files a family must recur across to become a candidate; default 3.
thresholdNoSimilarity threshold for grouping correction statements into rule families; default 0.22. Higher values yield fewer, tighter families.
include_sensitivityNoTrue (default) also returns how the family count changes across the 0.18-0.30 thresholds; false omits that curve.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.12.67
    • addedInput schema / properties / include_sensitivity / description
      Added value: +"True (default) also returns how the family count changes across the 0.18-0.30 thresholds; false omits that curve."
    • addedInput schema / properties / min_cards / description
      Added value: +"Minimum distinct cards a family must recur across to become a candidate; default 3."
    • addedInput schema / properties / min_files / description
      Added value: +"Minimum distinct files a family must recur across to become a candidate; default 3."
    • addedInput schema / properties / threshold / description
      Added value: +"Similarity threshold for grouping correction statements into rule families; default 0.22. Higher values yield fewer, tighter families."
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only declare readOnly and closed-world behavior, while the description adds substantial context: clustering rejection and invariant records by asserted rule, stripping instance vocabulary, recurrence thresholds, returned candidate card/request ids, blank draft dimensions, and activation gated on two actor identities. This is rich disclosure with no contradiction of the read-only annotation.

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?

Front-loads the purpose and gating, then adds only necessary behavioral detail in three short paragraphs. There is no filler, and the technical detail about rule clustering and activation gates earns its place.

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

Completeness5/5

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

For a complex mining and proposal tool, the description covers input behavior, the nature of returned candidates, and the activation constraints. The output schema carries return structure, so the description need not restate it.

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% and documents all four parameters, so the baseline is 3. The description reinforces the recurrence meaning of min_cards and min_files but says nothing about threshold or include_sensitivity beyond what the schema already provides.

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?

Opens with a specific verb and resource: 'mine the correction record into gated skill PROPOSALS.' It identifies manager-only read scope and clearly separates proposal generation from activation, so an agent can distinguish it from mutation and activation siblings.

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?

Describes the operational context: manager read-only mining, proposals not activations, and returned drafts only reach the store via the skill-proposal step. It states an exclusion (never activations) but does not name the closest sibling alternatives such as skill_add_evidence or skill_evidence_sweep or specify exact preconditions.

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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