AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sickn33/agentic-awesome-skills --skill agent-self-schedulinggit clone --depth 1 https://github.com/sickn33/agentic-awesome-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sickn33/agentic-awesome-skills/agent-self-scheduling)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/agent-self-scheduling"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/agent-self-scheduling/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/agent-self-scheduling"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/agent-self-scheduling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Excessive Agency · line 33 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
- high Excessive Agency · line 34 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
- medium Excessive Agency · line 49 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Rogue Agent · line 51 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.01164 |
| Opus 5 | $0.00012 | $0.00582 |
| Sonnet 5 | $0.00005 | $0.00233 |
| Haiku 4.5 | $0.00002 | $0.00116 |
Grade A, and why
agent-self-scheduling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
8 near-identical copies found in the catalogue:
- agent-self-scheduling — 100% identical, 0 lines differ
- agent-self-scheduling — 100% identical, 0 lines differ
- agent-self-scheduling — 100% identical, 0 lines differ
- agent-self-scheduling — 100% identical, 0 lines differ
- agent-self-scheduling — 100% identical, 0 lines differ
- agent-self-scheduling — 100% identical, 0 lines differ
- agent-self-scheduling — 92% identical, 33 lines differ
- agent-self-scheduling — 84% identical, 29 lines differ
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Self-Scheduling
When to Use
- Use when the user asks for recurring, scheduled, heartbeat, or looped agent work.
- Use when you need to choose between cron, external schedulers, hooks, or built-in agent scheduling.
First question: does the agent have a built-in scheduler (Hermes → Camp B), or do you own the clock (everything else → Camp A)?
Universal floor: cron is 1 minute minimum (5-field expr, no seconds) — every camp. For sub-minute you MUST use a while ...; sleep N; done loop, a TS extension, or an event hook. Never put an LLM on a tight timer.
Camp A — one-shot agents, you own the clock
These run once and exit (amnesiac unless resumed). Schedule them externally.
claude -p "PROMPT" --output-format json --allowedTools "Read,Edit,Bash" # Claude Code
codex exec --json "PROMPT" # Codex
pi run "PROMPT" # Pi
Wrap in a clock:
# 1. cron (>= 1 min floor)
*/10 * * * * cd /path/to/project && pi run "check X and report" >> ~/agent.log 2>&1
# 2. systemd timer (Linux, survives reboot, better logging) — OnUnitActiveSec=10min
# 3. dumb loop (sub-minute, or no cron available)
while true; do pi run "check X"; sleep 30; done
Gotchas (each breaks unattended runs if ignored):
- Permissions hang forever. Pass
--allowedTools(Claude) or sandbox/auto-approve flags (Codex), or the run blocks on a prompt. - Use JSON output (
--output-format json/--json) so the wrapper parses results deterministically. - Runs are amnesiac. Resume (
codex exec resume --last) or persist state to a file the next run reads.
Pi has NO built-in scheduler/loop/heartbeat by design — external clock only (or a TS extension for agent-side timers).
cmux — orchestration only, NO scheduler
cmux has no timer/watch/cron. Three ways to loop it: orchestrator-driven (send → sleep → read-screen on your own clock), a dumb while-sleep wrapper, or — preferred — event-driven via cmux notify + OSC terminal hooks, which is cheaper and more responsive than polling. read-screen is non-interruptive, safe to poll.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 89 lines · 24 tokens per session scan A 0f9fde1ddcc4
agent-self-scheduling is a skill published in the GitHub repository sickn33/agentic-awesome-skills (46,230 stars, last pushed yesterday), licensed MIT. It adds 24 tokens to every session and 1,164 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.
agent-self-scheduling
Schedule AI agent runs with cron, loops, or external clocks while avoiding unsafe tight autonomous timers.