agent-loop-ext
Crash-resilient external agent loop with state persistence and CI/CD integration
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.
$ npx -y skills add jmagly/aiwg --skill dataset-intelligence --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/dataset-intelligenceContext 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.
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]
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.
Repo: jmagly/aiwg
Crash-resilient external agent loop with state persistence and CI/CD integration
Detect requests for iterative autonomous agent loops and route to the appropriate loop executor
Automatically execute tests when code-generating agents modify source files, enforcing the execute-before-return pattern
Enable agent loops to learn from similar past tasks and share patterns across loops
Query and manage the executable feedback debug memory
Execute tests on generated code and iterate until passing