Automating Your Automations
SkillMonitoring & opsMine atuin history and shell logs to find repetitive workflows, build Rust CLI or bash automations. Use when analyzing command patterns or finding automation opportunities.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Automating Your Automations skill
What this skill tells your AI
The instructions your AI receives, as published by lev-os/agents in skills-db/_todo/automating-your-automations/SKILL.md and read by ahel’s review.
Core Insight: Your command history is a fossil record of automation opportunities. Every repeated multi-step workflow is a Rust CLI waiting to be born.
| Principle | Implication |
|---|---|
| Frequency x Pain = Priority | 3-command sequence 50x/week > 10-command sequence 1x/month |
| Complex → Rust; simple → bash | State, error handling, SQLite → Rust CLI. Glue → bash |
The Loop (Mandatory)
1. MINE → atuin DB, zsh_history, systemd timers, journalctl
2. CLUSTER → semantic similarity + temporal adjacency
3. SCORE → frequency × time_saved × error_rate
4. PROPOSE → Rust CLI vs bash script vs alias vs systemd timer
5. BUILD → /rust-cli-with-sqlite or bash in ~/.local/bin/
6. VALIDATE → 5x run, --dry-run, --robot JSON, ≥3x faster
7. INSTALL → systemd timer, shell alias, or PATH binary
Never skip 1-3. Intuition about what's repetitive is unreliable; data wins.
Step 1: Mine
Data Sources
| Source | Location | Unique Value |
|---|---|---|
| Atuin DB | ~/.atuin/history.db | Duration, exit codes, cwd, session grouping |
| zsh_history | ~/.zsh_history | Timestamps in extended format |
| Systemd | ~/.config/systemd/user/*.timer | Existing automation to audit |
| Journalctl | journalctl --user | Failure patterns |
| bash/git/cron | ~/.bash_history, git log, crontab -l | Fallback sources |
If ~/.atuin/history.db is missing, check XDG-style paths such as ~/.local/share/atuin/history.db before concluding Atuin is unavailable. If Atuin truly is unavailable, fall back to ~/.zsh_history / ~/.bash_history and downgrade confidence on timing/failure-rate scoring.
Essential Atuin Queries
Open read-only: sqlite3 -readonly ~/.atuin/history.db
If that path does not exist, discover the DB first:
find ~ ~/.local/share -maxdepth 3 \( -name 'history.db' -o -name '*atuin*' \) 2>/dev/null
Atuin stores timestamp and duration in nanoseconds. Exit 0 = success.
-- Top repeated commands
SELECT command, COUNT(*) as cnt, AVG(duration)/1e9 as avg_sec,
SUM(CASE WHEN exit != 0 THEN 1 ELSE 0 END) as fails
FROM history GROUP BY command HAVING cnt > 5 ORDER BY cnt DESC LIMIT 30;
-- Multi-step workflows (commands within 10s in same session/cwd)
SELECT h1.command as step1, h2.command as step2, COUNT(*) as pair_cnt
FROM history h1 JOIN history h2
ON h2.timestamp BETWEEN h1.timestamp AND h1.timestamp + 10000000000
AND h1.cwd = h2.cwd AND h1.session = h2.session AND h1.id != h2.id
GROUP BY step1, step2 HAVING pair_cnt > 3
ORDER BY pair_cnt DESC LIMIT 20;
-- High-failure commands (retry/guard candidates)
SELECT command, COUNT(*) as total,
ROUND(100.0 * SUM(CASE WHEN exit != 0 THEN 1 ELSE 0 END) / COUNT(*), 1) as fail_pct
FROM history GROUP BY command HAVING total > 5 AND fail_pct > 20
ORDER BY total DESC LIMIT 20;
Full cookbook (10 queries + export + analysis): ATUIN-QUERIES.md
THE EXACT PROMPT
Analyze my command history to find automation opportunities.
1. Query atuin DB: repeated commands, multi-step workflows,
high-failure commands, time-of-day patterns, retry patterns
2. Inspect systemd user timers for gaps and silent failures
3. Score each pattern: frequency × time_saved × error_rate
4. Output top 10 candidates with: pattern, frequency, time estimate,
recommended implementation (Rust/bash/alias/timer), complexity (S/M/L)
Step 2: Score
| Factor | Weight | Source |
|---|---|---|
| Frequency | 40% | COUNT(*) from atuin |
| Time saved | 30% | AVG(duration) × frequency |
| Error rate | 20% | fail_pct from atuin |
| Simplicity | 10% | Inverse of implementation complexity |
Score = freq_norm×0.4 + time_norm×0.3 + fail_norm×0.2 + simplicity_norm×0.1
Only automate if Score >= 0.3. Expanded 5-factor formula with normalization: PATTERN-DETECTION.md
Step 3: Propose
Stateful? (remembers across runs)
├─ YES → Rust CLI + SQLite (/rust-cli-with-sqlite)
│ ├─ Scheduled? → systemd timer
│ └─ Interactive? → clap subcommands + --robot JSON
└─ NO
├─ >3 steps? → bash script → ~/.local/bin/
├─ Retry/guard? → bash wrapper + set -euo pipefail
└─ Single command? → shell alias → ~/.zshrc.local
Step 4: Build
Rust CLIs — every automation CLI must have:
--robot/--jsonfor machine output--dry-runfor safe testing- Non-zero exit codes on failure
Scaffold template: RUST-SCAFFOLD.md
Bash scripts — always set -euo pipefail, install to ~/.local/bin/
Systemd timers — creation, activation, monitoring: SYSTEMD.md
Step 5: Validate
- Run 5x, compare output to manual execution
-
--dry-runproduces no side effects -
--robotoutput parses as valid JSON - Automated ≥ 3x faster than manual
- Force failure → verify graceful behavior
Anti-Patterns
| Don't | Instead |
|---|---|
| Automate before measuring | Run atuin queries first |
| Rust CLI for 2-line glue | Bash script or alias |
Skip --dry-run | Always add dry-run mode |
| Ignore exit codes | Non-zero exit + logging |
| Automate rare commands (Score < 0.3) | Skip — maintenance > benefit |
| One giant script | Unix philosophy: small composable tools |
Integration
| Need | Skill |
|---|---|
| Rust CLI + SQLite patterns | /rust-cli-with-sqlite |
| Search prior agent sessions | /cass |
| Turn automation into a skill | /sc + /sw |
| Track automation tasks | /br |
| Optimize slow commands | /extreme-software-optimization |
Reference Index
| Need | Read |
|---|---|
| Full atuin query cookbook (10 queries) | ATUIN-QUERIES.md |
| Shell history parsing (zsh/bash/fish) | SHELL-HISTORY.md |
| Systemd timers: create, audit, monitor | SYSTEMD.md |
| Rust CLI scaffold + Cargo.toml | RUST-SCAFFOLD.md |
| Real-world examples with scores | EXAMPLES.md |
| Clustering + scoring algorithms | PATTERN-DETECTION.md |
Done When
- Atuin DB queried for all pattern types
- Top candidates scored and ranked
- At least one automation built and validated
- Automation installed (PATH, alias, or systemd timer)
- Time savings measured
Signals
- GitHub stars
- 22
- Forks
- 2
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
automating-your-automations- Source
- github.com/lev-os/agents