Agent skill

Automation

by ginlix-ai in ginlix-ai/LangAlpha

Create and manage scheduled and price-triggered automations.

Apache-2.0Auto-check passed

Install Automation

skills CLI
$ npx skills add ginlix-ai/LangAlpha --skill automation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ginlix-ai/LangAlpha automation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ginlix-ai/LangAlpha.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/langalpha_service/skills/automation .claude/skills/automation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
automation
GitHub stars
1.8k
Token cost
~2.3k tokens
SKILL.md length
726 words
Files
1
Skills in repo
37
Repo updated
First seen
Licence
Apache-2.0

At a glance

Create and manage scheduled and price-triggered automations.

  • SKILL.md covers Before Creating an Automation, Tool 1: check_automations, Tool 2: create_automation and Price-Triggered Automations, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Automation is an agent skill from ginlix-ai/LangAlpha. Create and manage scheduled and price-triggered automations.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Claude Code for Financial Market. The licence is Apache-2.0.

Example prompts

  • “/automation”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 2855e43. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Automation loads about 2.3k tokens when it runs. Until then it costs about 18 tokens; SKILL.md has 726 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~18
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ginlix-ai/LangAlpha at commit 2855e43, republished under its Apache-2.0 licence (© ginlix-ai). 726 words, ~2,347 tokens.

Download SKILL.mdSave it as .claude/skills/automation/SKILL.md (or your agent's skills folder).
name
automation
description
Create and manage scheduled and price-triggered automations.

Automation Skill

This skill provides 3 tools for creating and managing scheduled automations:

  • check_automations - List all or inspect a specific automation
  • create_automation - Create a new scheduled automation
  • manage_automation - Update, pause, resume, trigger, or delete automations

Before Creating an Automation

Always confirm with the user before calling create_automation. Automations run autonomously on a schedule, so getting the details right matters. If the user's request is unclear or underspecified, ask to clarify:

  • Schedule — "Every morning" is ambiguous. Confirm the exact time and days (e.g. "Weekdays at 9 AM in your timezone?").
  • Thread strategy — If the task involves ongoing analysis or follow-ups, ask whether they want results in a fresh thread each time, a single persistent thread, or the current conversation.
  • Instruction — The instruction runs without further user input. If the user gives a vague prompt like "check my portfolio", refine it: what tickers? what metrics? what format?
  • Delivery — If the user hasn't mentioned how they want to receive results, ask if they want delivery (e.g. Slack) or just in-app.

Summarize what you're about to create and get a "yes" before calling the tool.


Tool 1: check_automations

List all automations or inspect a specific one with execution history.

ParameterTypeRequiredDescription
automation_idstrNoAutomation ID to inspect. Omit to list all.
Examples
python
# List all automations
check_automations()

# Inspect a specific automation (includes last 5 executions)
check_automations(automation_id="abc-123")

Tool 2: create_automation

Create a new scheduled automation.

ParameterTypeRequiredDescription
namestrYesShort name for the automation
instructionstrYesThe prompt the agent will execute on each run
schedulestrCron/onceCron expression or ISO datetime (see below). Omit for price triggers.
trigger_typestrNo"price" for a price trigger; otherwise inferred from schedule
trigger_configdictPriceSymbol and conditions (see Price-Triggered Automations)
descriptionstrNoOptional description
threadstrNo"new" (default), "persistent", or "current" (see Thread Strategy)
deliverystrNoComma-separated delivery methods (e.g. "slack")
Thread Strategy
ModeBehavior
"new"Fresh thread each run — no conversation history carried over (default)
"persistent"Single dedicated thread — all runs share conversation history
"current"Pins to the current conversation thread — automation runs continue here
Schedule Format
  • Recurring (cron): Standard 5-field cron expression
    • 0 9 * * 1-5 — weekdays at 9 AM
    • 0 */4 * * * — every 4 hours
    • 30 8 1 * * — 1st of each month at 8:30 AM
  • One-time (ISO datetime):
    • 2026-03-01T10:00:00 — single execution at that time
Examples
python
# Daily market briefing on weekdays at 9 AM
create_automation(
    name="Morning Market Brief",
    instruction="Summarize overnight market moves, top gainers/losers, and any news for my watchlist.",
    schedule="0 9 * * 1-5",
)

# One-time earnings reminder
create_automation(
    name="AAPL Earnings Reminder",
    instruction="Analyze AAPL ahead of earnings: recent price action, analyst expectations, key metrics to watch.",
    schedule="2026-04-30T08:00:00",
    description="Pre-earnings analysis for Apple Q2 2026",
)

# Daily report delivered to Slack
create_automation(
    name="Morning Market Brief",
    instruction="Summarize overnight market moves for my watchlist.",
    schedule="0 9 * * 1-5",
    delivery="slack",
)

# Automation with persistent thread (all runs share history)
create_automation(
    name="Weekly Portfolio Review",
    instruction="Review my portfolio performance and update the analysis.",
    schedule="0 9 * * 1",
    thread="persistent",
)

# Automation that continues in the current conversation
create_automation(
    name="Hourly Price Check",
    instruction="Check AAPL, MSFT, GOOGL prices and alert if any moved >2%.",
    schedule="0 * * * *",
    thread="current",
)

Price-Triggered Automations

In addition to cron/datetime schedules, automations can trigger when a stock price meets a specific condition. Set trigger_type="price" and provide a trigger_config dict instead of a schedule; passing both is refused.

symbol is a bare US stock or index ticker (AAPL, SPX), with no ^ or I: prefix. There is no crypto, currency or futures feed, so no alert can watch those.

Show full SKILL.md (286 more words)Show less
Condition Types
ConditionDescription
price_aboveFires when price rises above the given value
price_belowFires when price drops below the given value
pct_change_aboveFires when the price is up more than the given percent
pct_change_belowFires when the price is down more than the given percent. The value is positive: 3 means a 3% drop

For percentage conditions, reference sets the baseline price:

ReferenceDescription
previous_closePrior trading day's closing price (default)
day_openCurrent trading day's opening price
Retrigger Modes
ModeBehavior
one_shotTrigger once, then mark completed (default)
recurringRe-arm after cooldown. Omit cooldown_seconds for once-per-trading-day default, or set cooldown_seconds (min 14400 = 4 hours) for custom interval.
Examples
python
# Alert when AAPL drops below $150 (one-shot)
create_automation(
    name="AAPL Price Alert",
    instruction="AAPL has dropped below $150. Summarize recent news and analyst sentiment.",
    trigger_type="price",
    trigger_config={
        "symbol": "AAPL",
        "conditions": [{"type": "price_below", "value": 150}],
    },
)

# Run analysis when TSLA moves up 5% from yesterday's close
create_automation(
    name="TSLA Momentum Alert",
    instruction="TSLA is up 5% from yesterday's close. Analyze volume, technicals, and any catalysts.",
    trigger_type="price",
    trigger_config={
        "symbol": "TSLA",
        "conditions": [
            {"type": "pct_change_above", "value": 5, "reference": "previous_close"},
        ],
    },
)

# Recurring alert with 4-hour cooldown
create_automation(
    name="NVDA Volatility Watch",
    instruction="NVDA moved more than 3% from today's open. Summarize volume, options flow and news.",
    trigger_type="price",
    trigger_config={
        "symbol": "NVDA",
        "conditions": [
            {"type": "pct_change_above", "value": 3, "reference": "day_open"},
        ],
        "retrigger": {"mode": "recurring", "cooldown_seconds": 14400},
    },
)
Agent Guidelines for Price Triggers
  • Confirm before creating. Always repeat the symbol, condition, threshold value, and retrigger mode back to the user and get explicit confirmation.
  • Default to one_shot retrigger mode unless the user asks for repeated alerts. For recurring, omit cooldown_seconds to default to once per trading day.

Tool 3: manage_automation

Manage an existing automation.

ParameterTypeRequiredDescription
automation_idstrYesAutomation ID to manage
actionstrYesOne of: update, pause, resume, trigger, delete
namestrNoNew name (update only)
descriptionstrNoNew description (update only)
instructionstrNoNew prompt (update only)
schedulestrNoNew cron or ISO datetime (update only)
threadstrNo"new", "persistent", or "current" (update only)
deliverystrNoComma-separated delivery methods (update only)
remove_deliveryboolNoSet to true to remove delivery config (update only)
Action Reference
ActionDescription
updateChange name, description, instruction, schedule, thread strategy, or delivery
pauseTemporarily stop the automation from running
resumeRe-enable a paused automation
triggerRun the automation immediately (outside normal schedule)
deletePermanently remove the automation
Examples
python
# Pause an automation
manage_automation(automation_id="abc-123", action="pause")

# Resume it
manage_automation(automation_id="abc-123", action="resume")

# Trigger an immediate run
manage_automation(automation_id="abc-123", action="trigger")

# Update the schedule to run every Monday at 8 AM
manage_automation(
    automation_id="abc-123",
    action="update",
    schedule="0 8 * * 1",
)

# Switch an automation to a persistent thread
manage_automation(automation_id="abc-123", action="update", thread="persistent")

# Remove delivery from an automation
manage_automation(automation_id="abc-123", action="update", remove_delivery=True)

# Delete an automation
manage_automation(automation_id="abc-123", action="delete")

© ginlix-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/langalpha_service/skills/automation of ginlix-ai/LangAlpha.

Open the folder on GitHubat commit 2855e43

Compare with similar skills

Automation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Automation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Automation this skillginlix-ai/LangAlpha1.8k—~2.3kAutomated safety check: PassApache-2.0
Autom AutomationComposioHQ/awesome-claude-skills77k3 repos~723Automated safety check: PassNone
Doppler Marketing Automation AutomationComposioHQ/awesome-claude-skills77k3 repos~809Automated safety check: PassNone
Scheduleasgeirtj/system_prompts_leaks69k—~2.9kAutomated safety check: PassCC0-1.0
Scheduleasgeirtj/system_prompts_leaks69k—~597Automated safety check: PassCC0-1.0
Pricingsickn33/agentic-awesome-skills47k1 repos~1.9kAutomated safety check: PassMIT

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Questions about Automation

What does Automation do?

Create and manage scheduled and price-triggered automations. Automation is an agent skill from ginlix-ai/LangAlpha. Create and manage scheduled and price-triggered automations.

How do I install Automation in Claude Code?

Run `npx skills add ginlix-ai/LangAlpha --skill automation -a claude-code`. Or copy the skill folder (plugins/langalpha_service/skills/automation in ginlix-ai/LangAlpha) into .claude/skills/automation in your project. Claude Code loads it when a task matches its description.

How do I install Automation in Codex?

Run `npx skills add ginlix-ai/LangAlpha --skill automation -a codex`. Or copy the skill folder (plugins/langalpha_service/skills/automation in ginlix-ai/LangAlpha) into .agents/skills/automation in your project. Codex loads it when a task matches its description.

Can I use Automation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ginlix-ai/LangAlpha --skill automation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/automation, .gemini/skills/automation, .github/skills/automation and .opencode/skills/automation in your project.

What does Automation need to run?

SKILL.md names no scripts, command-line tools or credentials: Automation is instructions for the agent only. Our summary lists: Python 3.

Does Automation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Automation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Automation use?

Automation is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Automation use?

About 2.3k tokens (SKILL.md is roughly 9.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Automation?

Skills that share tags, products or a category with Automation: Autom Automation (ComposioHQ/awesome-claude-skills, 77k stars), Doppler Marketing Automation Automation (ComposioHQ/awesome-claude-skills, 77k stars), Schedule (asgeirtj/system_prompts_leaks, 69k stars) and Schedule (asgeirtj/system_prompts_leaks, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Automation?

ginlix-ai (a GitHub organization) maintains it in ginlix-ai/LangAlpha, which has 1,811 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on October 10, 2026.

Source: ginlix-ai/LangAlpha on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.