Shows learned instincts from dqiii8.db, grouped by project and confidence. Internal diagnostic tool — not for user invocation.
Scanned 6/6/2026
Install via CLI
openskills install senda-labs/DQIII8---
name: instinct-status
description: Shows learned instincts from dqiii8.db, grouped by project and confidence. Internal diagnostic tool — not for user invocation.
command: /instinct-status
allowed-tools: [Bash]
user-invocable: false
---
# /instinct-status — Instinct Status
Shows continuous learning instincts stored in `dqiii8.db`.
## Usage
```
/instinct-status
/instinct-status --project dqiii8-core
/instinct-status --top 10
```
## What it does
1. Reads the `instincts` table from `database/dqiii8.db`
2. Groups by project (project-scoped first, then global)
3. Shows confidence bar + times applied
4. Highlights high-confidence instincts (>0.7) as "consolidated"
## Implementation
```bash
python3 -c "
import sqlite3, os, sys
DB = 'database/dqiii8.db'
project_filter = None
top_n = 20
# Parse args (passed as ARGS env or argv)
args = sys.argv[1:]
for i, a in enumerate(args):
if a == '--project' and i+1 < len(args):
project_filter = args[i+1]
if a == '--top' and i+1 < len(args):
top_n = int(args[i+1])
conn = sqlite3.connect(DB)
if project_filter:
rows = conn.execute(
'SELECT keyword, pattern, confidence, times_applied, times_successful, project, created_at '
'FROM instincts WHERE project=? ORDER BY confidence DESC LIMIT ?',
(project_filter, top_n)
).fetchall()
else:
rows = conn.execute(
'SELECT keyword, pattern, confidence, times_applied, times_successful, project, created_at '
'FROM instincts ORDER BY project, confidence DESC LIMIT ?',
(top_n,)
).fetchall()
conn.close()
if not rows:
print('No instincts registered yet.')
print('They will be generated automatically at the end of sessions with corrections in tasks/lessons.md')
exit(0)
def conf_bar(c):
filled = int(c * 10)
return 'X' * filled + '.' * (10 - filled) + f' {int(c*100)}%'
print('=' * 60)
print(f' INSTINCT STATUS -- {len(rows)} total')
print('=' * 60)
current_proj = '__none__'
for kw, pattern, conf, applied, successful, proj, created in rows:
if proj != current_proj:
current_proj = proj
label = proj if proj else 'GLOBAL'
print(f'\n## {label.upper()}')
bar = conf_bar(conf or 0)
success_pct = int((successful or 0) / max(applied or 1, 1) * 100)
tag = ' consolidated' if (conf or 0) >= 0.7 else ''
print(f' {bar} [{kw}]{tag}')
print(f' applied: {applied or 0}x successful: {success_pct}% since: {(created or \"\")[:10]}')
if pattern:
preview = pattern[:80] + ('...' if len(pattern) > 80 else '')
print(f' {preview}')
"
```
## Notes
- Source: `database/dqiii8.db` table `instincts`
- Updated in each stop.py when there are new lessons in `tasks/lessons.md`
- Lesson format for parsing: `[YYYY-MM-DD] [KEYWORD] cause → fix`
- To view full history: `python3 -c "import sqlite3; ..."`
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