Files
boocode/data/skills/boocode/self-healing/scripts/find-similar-heals.sh
indifferentketchup 9abc14ef82 feat(skills): add self-healing and verify-gate skills from pskoett-skills fork
Self-healing: heal loop with verify-before-persist discipline, Pattern-Key
dedup, HEAL entry format, 3 scripts, examples reference, eval.yaml.
Verify-gate: 4-step process (Discover -> Run -> Fix Loop -> Gate Signal)
with 3-attempt fix loop, scope-to-fix-only discipline, command discovery.
.learnings/HEALS.md with template entry.
2026-06-07 23:17:33 +00:00

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#!/usr/bin/env bash
# find-similar-heals.sh — Search existing heals before generating a new fix.
# Usage: ./find-similar-heals.sh <pattern-key-or-keyword>
#
# Prints matching HEAL entries with their Pattern-Key, Status, and Recurrence-Count
# so the agent can decide whether to re-apply an existing fix or write a new one.
set -euo pipefail
QUERY="${1:-}"
HEALS_FILE="$(pwd)/.learnings/HEALS.md"
if [[ -z "$QUERY" ]]; then
echo "usage: $0 <pattern-key-or-keyword>" >&2
exit 2
fi
if [[ ! -f "$HEALS_FILE" ]]; then
echo "(no .learnings/HEALS.md yet — no prior heals to consult)"
exit 0
fi
# Find HEAL section headers that contain the query in their body (Pattern-Key, name, or text).
python3 - <<PY "$QUERY" "$HEALS_FILE"
import sys, re
query, path = sys.argv[1].lower(), sys.argv[2]
with open(path) as f:
text = f.read()
# Split into entries by ^## [HEAL-...]
entries = re.split(r"(?m)^## \[HEAL-", text)[1:]
hits = []
for body in entries:
if query in body.lower():
head = body.splitlines()[0]
pk = re.search(r"Pattern-Key:\s*(\S+)", body)
status = re.search(r"Status\*\*:\s*(\S+)", body) or re.search(r"Status:\s*(\S+)", body)
rc = re.search(r"Recurrence-Count:\s*(\d+)", body)
hits.append({
"id": "HEAL-" + head.split("]")[0],
"name": head.split("]", 1)[1].strip() if "]" in head else head,
"pattern_key": pk.group(1) if pk else "?",
"status": status.group(1) if status else "?",
"recurrence": rc.group(1) if rc else "1",
})
if not hits:
print(f"(no heals match '{query}')")
else:
print(f"Found {len(hits)} matching heal(s):\n")
for h in hits:
print(f" {h['id']} {h['name']}")
print(f" pattern={h['pattern_key']} status={h['status']} recurrence={h['recurrence']}")
PY