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/dataset-intelligence

Route any dataset, custom indexing, traceability, provenance, lineage, synchronization, or retirement request through one governed workflow. Use when a user points AIWG at data and wants an outcome without knowing schema or indexing terminology.

From plugin
aiwg
211200 skills199 agents26 commands
Install
$ npx -y skills add jmagly/aiwg --skill dataset-intelligence --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/dataset-intelligence

Context preview

The summary Claude sees to decide when to auto-load this skill.

Route any dataset, custom indexing, traceability, provenance, lineage, synchronization, or retirement request through one governed workflow. Use when a user points AIWG at data and wants an outcome without knowing schema or indexing terminology.

SKILL.md

dataset-intelligence.SKILL.md
namespace: aiwg
name: dataset-intelligence
description: Route any dataset, custom indexing, traceability, provenance, lineage, synchronization, or retirement request through one governed workflow. Use when a user points AIWG at data and wants an outcome without knowing schema or indexing terminology.
version: 1.0.0
platforms: [all]
kernel: true
aliases: [dataset, data steward, data onboarding, custom indexing, dataset workflow]
triggers: [use this data, make this searchable, index my files, build a knowledge index, trace this dataset, show data provenance, sync this source, retire this dataset, point AIWG at data, use a dataset offline, write a source adapter, migrate index graphs]

Dataset Intelligence Router

Ask only for the source path or URI and desired outcome if they are not already present. Do not require the user to choose a schema, adapter, backend, index, or provenance vocabulary.

1. Invoke `dataset-intake` and return a concise recommendation containing: assumptions, rationale, privacy/locality/network implications, materialized artifacts, and safe defaults. 2. Route assessment to `dataset-source-assess`, capability composition to `dataset-capability-recommend`, and approval preparation to `dataset-plan-review`. 3. Route an approved plan to `dataset-ingest`; route inspection to `dataset-trace` or `dataset-verify`; route portable output to `dataset-export`; route removal to `dataset-retire`. 4. Carry stable intake, plan, run, checkpoint, approval, verification, and evidence references between phases. Never rely on conversation state as the record of authority.

Every operational step delegates to `aiwg dataset`. This router must not read a source, execute a connector, write an index, advance a checkpoint, or delete data. Indexes and Fortemi shards are derived, never canonical persistence.

SDLC, research, knowledge-base, media, marketing, ops, and project-local callers all use the same intake and handoff contracts; domain additions are namespaced.

Read more
Ships withaiwg

Reusable project context and specialist workflows for the AI tools you already use. Plan software, coordinate specialist reviews, prepare campaigns, investigate incidents, organize research, curate media, and maintain operational knowledge.

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