/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.
Claude Code
$ npx -y skills add jmagly/aiwg --skill dataset-intelligence --agent claude-code
Codex
$ npx skills add jmagly/aiwg --skill dataset-intelligence -a codex -y
Cursor
$ npx skills add jmagly/aiwg --skill dataset-intelligence -a cursor -y
Gemini CLI
$ npx skills add jmagly/aiwg --skill dataset-intelligence -a gemini-cli -y
GitHub Copilot
$ npx skills add jmagly/aiwg --skill dataset-intelligence -a github-copilot -y
OpenCode
$ npx skills add jmagly/aiwg --skill dataset-intelligence -a opencode -y
Windsurf
$ npx skills add jmagly/aiwg --skill dataset-intelligence -a windsurf -y
SKILL.md
dataset-intelligence.SKILL.mdnamespace: 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
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.
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.
Other skills on aiwg.
More skills from other plugins.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
ask-matt
Ask which skill or flow fits your situation. A router over the skills in this repo.
Questions about dataset-intelligence.
- Which coding agents can use dataset-intelligence?
- dataset-intelligence installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

