Agent skill

comprehensive-learning

Single fire-and-forget command that runs the full session learning pipeline: insights → reflect → knowledge → improve → action-candidates → report. All machines run local Phases 1–9 against logs/orchestrator/ and commit derived state. dev-primary additionally runs Phase 10a (cross-machine compilation) and Phase 10 (report). Safe for cron scheduling. Use when session ends, nightly cron fires, or you want to harvest learnings from recent sessions. Replaces running 4 skills manually.

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Install this agent skill to your Project

npx add-skill https://github.com/vamseeachanta/workspace-hub/tree/main/.claude/skills/workspace-hub/comprehensive-learning

SKILL.md

comprehensive-learning — Session Learning Pipeline

Single fire-and-forget skill running Phases 1–9 on all machines and Phases 10a+10 (cross-machine compilation + report) on dev-primary only.

Full phase specs: references/pipeline-detail.md — read it when you need signal sources, extraction rules, candidate formats, or state file details.

Mode-Based Routing

bash
MACHINE=$(hostname -s 2>/dev/null || hostname | cut -d. -f1 | tr '[:upper:]' '[:lower:]')
case "$MACHINE" in
  dev-primary) CL_MODE="full" ;;
  dev-secondary) CL_MODE="contribute" ;;
  licensed-win-1|licensed-win-2) CL_MODE="contribute" ;;
  *) CL_MODE="contribute" ;;
esac
# All modes run Phases 1–9. Only 'full' runs Phase 10a (compilation) + Phase 10 (report).

Cross-Machine Data Flow

Machine Commits Notes
dev-secondary candidates/, corrections/, patterns/, session-signals/ Open-source CFD/dev
licensed-win-1 candidates/, corrections/, session-signals/, patterns/ OrcaFlex/ANSYS
licensed-win-2 candidates/ Windows; no AI CLIs

dev-primary git pull in Phase 10a picks up all machines' committed derived state.

Pipeline Summary

Run phases sequentially. Non-mandatory phases log failure and continue. Fatal failures in Phases 1 or 4 set _PIPELINE_EXIT=1. Phase 10 always runs via trap EXIT.

Phase Name Mandatory Short description
1 Insights Extract skill usage, tool patterns, session-quality signals from all log sources
1b Drift Detection dev-primary Detect python_runtime/file_placement/git_workflow violations in yesterday's log
2 Reflect Invoke /reflect against reflect-history/ and trends/
3 Knowledge Invoke /knowledge; update patterns/
3b Memory Compaction Compact MEMORY.md + topic files
3c Memory Curation Promote stable patterns, expire stale entries
4 Improve Invoke /improve; update skills + rules from candidates/
5 Correction Trends Analyze corrections/ for recurring failure patterns
6 WRK Feedback + Ecosystem WRK quality review + skill usage frequency + ecosystem health
7 Action Candidates Convert candidates/ entries to WRK items
8 Report Review Review learning report for coherence
9 Skill Coverage Audit weekly Audit skill coverage via identify-script-candidates.sh + skill-coverage-audit.sh; include tier distribution from skill-tier-report.py (A/B/C/D per config/skills/quality-tiers.yaml)
10a Cross-Machine Compile full only git pull + aggregate from all machines
10 Report always Write report (trap EXIT)

For phase details (signal sources, extraction rules, YAML formats): → read references/pipeline-detail.md

Session Design: Lean by Default

Sessions are pure multi-agent execution engines — all brain directed at the task. Analysis, maintenance, and learning are deferred to the nightly run.

In-session Nightly pipeline
WRK gate check + active-wrk set All insight/reflect/knowledge/improve runs
Multi-agent implementation Correction trend analysis
Fast signal capture (hooks write raw signals) Candidate → WRK auto-creation
/session-start context load Memory and skill file updates
Cross-review (Codex gate) Ecosystem health checks
Commit + push Session archive rsync

Must NOT run standalone during sessions: /insights, /reflect, /knowledge, /improve, consume-signals.sh heavy analysis, ecosystem-health-check.sh, session-end-evaluate.sh scoring.

Stop hooks: one hook only, raw write, < 1 second. See WRK-304.

Scheduling

Crontab entry (dev-primary, 22:00 nightly):

bash
0 22 * * * cd /mnt/local-analysis/workspace-hub && \
  bash scripts/cron/comprehensive-learning-nightly.sh \
  >> .claude/state/learning-reports/cron.log 2>&1

Script: scripts/cron/comprehensive-learning-nightly.shgit pull is a hard gate; each rsync is independently || true.

Related

  • workstations skill: machine registry and cron_variant fields
  • WRK-299: implementation tracking | WRK-304: Stop hook cleanup | WRK-305: signal emitters
  • WRK-303: Ensemble planning → Planning Quality Loop (in references/pipeline-detail.md)
  • /insights, /reflect, /knowledge, /improve: individual pipeline stages
  • scripts/planning/ — ensemble planning outputs harvested by Planning Quality Loop

Iron Law

No learning pipeline phase (/insights, /reflect, /knowledge, /improve) shall run standalone during an active work session — learning is deferred to the nightly pipeline, always.

Rationalization Defense

Excuse Reality
"I'll just run a quick /reflect to capture this insight" /reflect consumes significant context and token budget. The nightly pipeline captures the same signals from hooks and logs — for free.
"The session is almost over, might as well run /improve now" "Almost over" is when context is most valuable. Defer to nightly; hooks already captured the raw signals.
"This learning will be lost if I don't process it now" Stop hooks write raw signals in < 1 second. The nightly pipeline processes them. Nothing is lost by deferring.
"The nightly cron might not run tonight" Fix the cron job, do not work around it by running learning mid-session. Two problems are worse than one.

Red Flags

These phrases signal you are about to violate the Iron Law:

  • "let me quickly run /insights before we continue"
  • "I should capture this learning now"
  • "running /improve won't take long"
  • "the session is winding down anyway"

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