feat: operational self-improvement — every skill learns from failures

Adds universal operational learning capture to the preamble completion protocol.
At the end of every skill session, the agent reflects on CLI failures, wrong
approaches, and project quirks, logging them as type "operational" to the
learnings JSONL. Future sessions surface these automatically.

- generateCompletionStatus(ctx) now includes operational capture section
- Preamble bash shows top 3 learnings inline when count > 5
- New "operational" type in generateLearningsLog alongside pattern/pitfall/etc
- Updated unit tests + operational seed entry in learnings E2E

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Garry Tan
2026-03-29 21:04:35 -07:00
parent b6fcfd84b7
commit cade276c20
30 changed files with 594 additions and 8 deletions
+21
View File
@@ -65,6 +65,9 @@ _LEARN_FILE="${GSTACK_HOME:-$HOME/.gstack}/projects/${SLUG:-unknown}/learnings.j
if [ -f "$_LEARN_FILE" ]; then
_LEARN_COUNT=$(wc -l < "$_LEARN_FILE" 2>/dev/null | tr -d ' ')
echo "LEARNINGS: $_LEARN_COUNT entries loaded"
if [ "$_LEARN_COUNT" -gt 5 ] 2>/dev/null; then
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 3 2>/dev/null || true
fi
else
echo "LEARNINGS: 0"
fi
@@ -265,6 +268,24 @@ ATTEMPTED: [what you tried]
RECOMMENDATION: [what the user should do next]
```
## Operational Self-Improvement
Before completing, reflect on this session:
- Did any commands fail unexpectedly?
- Did you take a wrong approach and have to backtrack?
- Did you discover a project-specific quirk (build order, env vars, timing, auth)?
- Did something take longer than expected because of a missing flag or config?
If yes, log an operational learning for future sessions:
```bash
~/.claude/skills/gstack/bin/gstack-learnings-log '{"skill":"SKILL_NAME","type":"operational","key":"SHORT_KEY","insight":"DESCRIPTION","confidence":N,"source":"observed"}'
```
Replace SKILL_NAME with the current skill name. Only log genuine operational discoveries.
Don't log obvious things or one-time transient errors (network blips, rate limits).
A good test: would knowing this save 5+ minutes in a future session? If yes, log it.
## Telemetry (run last)
After the skill workflow completes (success, error, or abort), log the telemetry event.