Resume the requested analysis

SkillDev tools

Resume a specifically identified analysis using its verified run-local artifacts and controller state.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Resume the requested analysis skill

What this skill tells your AI

The instructions your AI receives, as published by ai-analyst-lab/ai-analyst in .claude/skills/resume-pipeline/SKILL.md and read by ahel’s review.

  1. Identify the exact run. Inspect question, inputs, plan and status. If several match, ask which one. A latest link does not select the user's intended work.
  2. Version 3 state uses helpers.pipeline.controller.Controller. Never overwrite or reinterpret legacy state as version 3. Offer a new run with explicitly selected, verified legacy artifacts while retaining the originals.
  3. For blocked approval gates, show evidence and request approval. Record it only after receiving it, with checkpoint, actor and reason. Local records are not authenticated identities.
  4. For failures, inspect the cause before retrying. Confirm an interrupted worker is no longer running. Never remove a lock while another controller is active.
  5. Run python -m helpers.pipeline.controller run EXACT_RUN_DIRECTORY, with --retry-failed only for an intentional retry. Code validates definition and artifact hashes and skips valid completed work. Changed definitions/artifacts require a new reviewed run; do not silently reuse stale work.
  6. Report the actual final status and outputs. Never manually change statuses or create a deck for a plan that did not request one.

Authentication, tool permissions and workflow approvals are separate requirements. See docs/PIPELINE-CONTROLLER.md for recovery and migration details.

Signals

GitHub stars
297
Forks
137
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
resume-pipeline
Source
github.com/ai-analyst-lab/ai-analyst