cron-management

Imported from xuiltul/animaworks (templates/en/common_skills/cron-management/SKILL.md). Install upstream with npx skills add xuiltul/animaworks --skill cron-management. Copyright stays with the author.

cron.md Structure

Overall Structure

# Cron: {your_name}

## Task Name 1
schedule: 0 9 * * *
type: llm
Task description...

## Task Name 2
schedule: */5 * * * *
type: command
command: /path/to/script.sh

Rules You MUST Follow

1. Each task must start with ## Task Name (H2 header. Do not use H3 or H1)
2. schedule: line is required (must start with schedule: keyword. Not a ### header)
3. Schedule must be standard 5-field cron expression only (09:00 or every Friday 17:00 are invalid)
4. type: line is required (llm or command)
5. Insert blank lines between tasks (for readability)

Invalid Formats

❌ ### */5 * * * *           ← Do NOT write cron expression as H3 header
❌ ### 09:00                 ← Natural language time is invalid
❌ ### Every Friday 17:00    ← Natural language schedule is invalid
❌ cron: 0 9 * * *           ← Key name must be "schedule:" (not "cron:")
❌ interval: 5m              ← Interval format is invalid
❌ schedule: 0 9 * * * *     ← 6 fields are invalid (5 fields only)

Valid Format

✅ schedule: 0 9 * * *       ← "schedule:" + space + 5-field cron expression
✅ schedule: */5 * * * *
✅ schedule: 30 21 * * *
✅ schedule: 0 17 * * 5

5-Field Cron Expression Reference

Field Structure

schedule: minute hour day month weekday

Note: Weekday is 0=Monday, 6=Sunday (APScheduler spec. Differs from standard cron where 0=Sunday)

Special Characters

Common Schedule Examples

Daily

Intervals

Weekday

Monthly

Task Type Details

type: llm — LLM Judgment Task

Tasks that require thinking and judgment. After schedule: and type: llm, write the task content in free form.

## Morning Planning
schedule: 0 9 * * *
type: llm
Check yesterday's progress from long-term memory and plan today's tasks.
Determine priorities based on vision and goals.
Write the result to state/current_state.md.

• The description is passed directly as the LLM prompt
• Stating the concrete output (what to write) is effective
• Multiple lines are allowed

type: command — Command Execution Task

Deterministic execution of bash commands or tool calls.

Pattern A: bash command

## Backup Execution
schedule: 0 2 * * *
type: command
command: /usr/local/bin/backup.sh

• Write the command in one line under command:
• Shell redirection (>, >>, |) is allowed
• Multi-line commands are discouraged (combine into one line or use a script file)

Pattern B: Tool invocation

## Slack Morning Greeting
schedule: 0 9 * * 0-4
type: command
tool: slack_send
args:
  channel: "#general"
  message: "Good morning!"

• tool: contains the tool name (schema name from get_tool_schemas())
• args: and below are YAML block format with 2-space indent
• Executed via dispatch(tool_name, args)

Option: skip_pattern

Skip LLM analysis session when command stdout matches a pattern.

## Chatwork Unreplied Check
schedule: */5 * * * *
type: command
command: chatwork_cli.py unreplied --json
skip_pattern: ^\[\]$

• skip_pattern: contains a regex
• In the example above, skips when unreplied count is 0 ([])

Option: trigger_heartbeat

Per-task control of whether to trigger LLM analysis session on command output.

## Chatwork Unreplied Check
schedule: */15 * * * *
type: command
command: animaworks-tool chatwork unreplied
skip_pattern: ^\[\]$
trigger_heartbeat: false

• trigger_heartbeat: false — Skip LLM analysis even when output exists
• trigger_heartbeat: true (default) — Analyze and respond in cron LLM session when output exists
• false, no, 0 suppress LLM analysis. Anything else is treated as true
• Can be used with skip_pattern. trigger_heartbeat: false is evaluated before skip_pattern
• LLM analysis session has Heartbeat-equivalent context (memory, Knowledge, org info)

Choosing Task Type

Use type: command when

• The command to execute is fully determined
• Parameters are fixed (region, cluster name, profile, etc.)
• Let the cron LLM session handle result interpretation

Use type: llm when

• Execution content must vary by situation
• Multiple tools need to be combined for investigation
• Human-like judgment or analysis is needed at execution time

Forbidden Patterns

• Including fixed commands in type: llm → That command should be type: command
• Writing "execute exactly this" but using type: llm → LLM cannot reliably reproduce commands. Use type: command

Anima is Not a "Command Memorizer"

type: command is like a human saving a script. Anima's value lies in judging and analyzing results. Let the framework handle deterministic execution, and let Anima focus on judgment, analysis, and reporting.

cron.md Operations

Add New Task

1. Read your cron.md
2. Add a new section at the end of the file
3. Verify format before writing (see checklist below)
4. Write the file

## New Task Name
schedule: <5-field cron expression>
type: llm|command
<description or command/tool lines>

Update Existing Task

1. Read cron.md
2. Locate the section (## Task Name to before next ##)
3. Edit the lines (schedule:, type:, description, etc.)
4. Write the file

Remove Task

1. Read cron.md
2. Delete the entire section (## Task Name to before next ##)
3. Write the file

Temporarily Disable Task

Wrap in HTML comment so the parser skips it:

<!--
## Paused Task
schedule: 0 9 * * *
type: llm
This task is temporarily paused.
-->

Pre-Write Checklist

Always verify the following before updating cron.md:

• Each task starts with ## Task Name (not ### or #)
• schedule: line exists (not ### header or natural language)
• Schedule is 5-field cron (minute hour day month weekday)
• Each field value is in valid range (min: 0-59, hour: 0-23, day: 1-31, month: 1-12, weekday: 0-6)
• type: line exists (llm or command)
• For command type, command: or tool: exists
• For tool type, args: indent is correct (2 spaces)
• Blank lines between tasks

Validation

After writing, you can verify parsing with:

python -c "
from core.supervisor.schedule_parser import parse_cron_md, parse_schedule
import pathlib

content = pathlib.Path('$ANIMAWORKS_ANIMA_DIR/cron.md').read_text()
tasks = parse_cron_md(content)
for t in tasks:
    trigger = parse_schedule(t.schedule)
    status = '✅' if trigger else '❌ parse failed'
    print(f'{status} {t.name}: schedule=\"{t.schedule}\" type={t.type}')
")

If all tasks show ✅, it is valid. Fix schedule expressions for any ❌.

Full Example

# Cron: example_anima

## Morning Planning
schedule: 0 9 * * *
type: llm
Check yesterday's progress from long-term memory and plan today's tasks.
Determine priorities based on vision and goals.
Write the result to state/current_state.md.

## Chatwork Unreplied Check
schedule: */5 9-18 * * 0-4
type: command
command: chatwork-cli unreplied --json > $ANIMAWORKS_ANIMA_DIR/state/chatwork_unreplied.json
skip_pattern: ^\[\]$
trigger_heartbeat: false

## Slack Morning Greeting
schedule: 0 9 * * 0-4
type: command
tool: slack_send
args:
  channel: "#general"
  message: "Good morning! Looking forward to working with you today."

## Weekly Reflection
schedule: 0 17 * * 4
type: llm
Re-read episodes/ from this week, extract patterns, and integrate into knowledge/.
Add procedures to procedures/ if improvements exist.

## Monthly Report
schedule: 0 10 1 * *
type: llm
Analyze episodes/ and knowledge/ from last month and create a monthly summary report.
Save the report as knowledge/monthly_report_YYYY-MM.md.

Common Mistakes and Fixes

Notes

• cron.md changes take effect on server restart or next Heartbeat (not immediate)
• Timezone is configurable via config.json system.timezone. Default: auto-detected from system
• Multiple tasks at the same time run in parallel
• Command-type task failures do not stop the server (logged)
• LLM-type tasks use the current model config from status.json
• When accessing other Anima's tools/ directory, verify permissions first