Identify tasks that waste tokens. Scripts don't hallucinate, don't cost per-run, and don't fail randomly. Spot automation opportunities and build them.
--- name: Automate description: Identify tasks that waste tokens. Scripts don't hallucinate, don't cost per-run, and don't fail randomly. Spot automation opportunities and build them. --- ## Core Principle LLMs are expensive, slow, and probabilistic. Scripts are free, fast, and deterministic. Every time you do something twice that could be scripted, you're wasting: - **Tokens** — money burned on solved problems - **Time** — seconds/minutes vs milliseconds - **Reliability** — LLMs fail randomly, scripts fail predictably Check `signals.md` for detection patterns. Check `templates.md` for common script patterns. --- ## The Automation Test Before doing any task, ask: 1. **Is this deterministic?** Same input → same output every time? 2. **Is this repetitive?** Will this happen again? 3. **Is this rule-based?** Can I write down the exact steps? If yes to all three → **script it, don't LLM it.** --- ## Script vs LLM Decision Matrix | Task type | Script | LLM | |-----------|--------|-----| | Format conversion (JSON↔YAML) | ✅ | ❌ | | Text transformation (regex) | ✅ | ❌ | | File operations (rename, move) | ✅ | ❌ | | Data validation | ✅ | ❌ | | API calls with fixed logic | ✅ | ❌ | | Git workflows | ✅ | ❌ | | Judgement calls | ❌ | ✅ | | Creative content | ❌ | ✅ | | Ambiguous inputs | ❌ | ✅ | | One-time unique tasks | ❌ | ✅ | --- ## Automation Triggers When you notice yourself: - Doing the **same task twice** → script it - Writing **similar prompts repeatedly** → script the pattern - **Formatting output** the same way → script the formatter - **Validating data** with same rules → script the validator - **Calling APIs** with predictable logic → script the integration --- ## Automation Proposal Format When you spot an opportunity: ``` 🔧 Automation opportunity Task: [what you keep doing] Frequency: [how often] Current cost: [tokens/time per run] Proposed script: - Language: [bash/python/node] - Input: [what it takes] - Output: [what it produces] - Location: [where to save it] Estimated savings: [tokens/time saved per month] Should I write it? ``` --- ## Script Standards When writing automation: 1. **Single purpose** — one script, one job 2. **Idempotent** — safe to run multiple times 3. **Documented** — usage in comments at top 4. **Logged** — output what you're doing 5. **Fail loud** — exit codes, error messages 6. **No secrets hardcoded** — env vars or keychain --- ## Tracking Automations Document what you've built: ``` ### Active Scripts - scripts/format-json.sh — JSON prettifier [saved ~2k tokens/week] - scripts/deploy-staging.sh — one-command deploy [saved 5min/deploy] - scripts/sync-env.sh — env file sync [eliminated manual errors] ### Candidates - Weekly report generation — repetitive formatting - Log parsing — same grep patterns every time ``` --- ## The 3x Rule If you do something **3 times**, it must become a script. - 1st time: Do it, note that it might repeat - 2nd time: Do it, flag as automation candidate - 3rd time: Stop. Write the script first, then run it. --- ## Anti-Patterns | Don't | Do instead | |-------|------------| | Re-prompt for same transformation | Write a script once | | Use LLM for data validation | Write validation rules | | Burn tokens on formatting | Use formatters (prettier, jq, etc.) | | Ask LLM to remember procedures | Document in scripts | | Solve same problem differently each time | Standardize with automation | --- *Every script written = permanent token savings. Compound your efficiency.*
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