agent-loop-ext
Crash-resilient external agent loop with state persistence and CI/CD integration
Turn a source path or URI and desired outcome into a governed dataset intake envelope for any AIWG domain.
$ npx -y skills add jmagly/aiwg --skill dataset-intake --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/dataset-intakeContext preview
The summary Claude sees to decide when to auto-load this skill.
Turn a source path or URI and desired outcome into a governed dataset intake envelope for any AIWG domain.
namespace: aiwg name: dataset-intake description: Turn a source path or URI and desired outcome into a governed dataset intake envelope for any AIWG domain. version: 1.0.0 platforms: [all] aliases: [data onboarding, dataset onboarding, source intake] triggers: [use this customer export, onboard this dataset, use these files, ingest this corpus, connect this data source]
Accept a source path/URI and desired outcome. Default the calling domain to `project-local`; SDLC, research, knowledge-base, media, marketing, and ops use the same envelope and may add only namespaced extensions.
Create a `dataset-intake/v1` envelope without opening the source. Record opaque source locator, outcome, domain, known privacy/locality/network constraints, authorization references, and independently requested capabilities (`search`, `traceability`, `provenance`, `graph`, `export`). Do not infer credential values. Then propose `aiwg dataset preview <source> --json` and hand the intake reference to `dataset-source-assess`.
For a question about existing normalized AI session history, route inspection to `session-explore` before proposing a new dataset. A separately requested export or derived index can enter this intake using its approved source/evidence references, privacy constraints and intended outcome. Do not scan provider homes or treat catalog inspection as approval to copy transcripts into another store.
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