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Automate

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.

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High Signal

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.

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
SKILL.md, signals.md, templates.md

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 9 sections Open source page

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: Is this deterministic? Same input → same output every time? Is this repetitive? Will this happen again? 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 typeScriptLLMFormat 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: Single purpose — one script, one job Idempotent — safe to run multiple times Documented — usage in comments at top Logged — output what you're doing Fail loud — exit codes, error messages 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'tDo insteadRe-prompt for same transformationWrite a script onceUse LLM for data validationWrite validation rulesBurn tokens on formattingUse formatters (prettier, jq, etc.)Ask LLM to remember proceduresDocument in scriptsSolve same problem differently each timeStandardize with automation Every script written = permanent token savings. Compound your efficiency.

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
3 Docs
  • SKILL.md Primary doc
  • signals.md Docs
  • templates.md Docs