Borrowing it
Nothing to install: this file belongs to Minh-Tam-Solution/tinysdlc. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Minh-Tam-Solution/tinysdlc/main/.agents/skills/schedule/SKILL.mdgit clone --depth 1 https://github.com/Minh-Tam-Solution/tinysdlcWrote 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/minh-tam-solution/tinysdlc/schedule)<a href="https://agentmods.dev/skills/minh-tam-solution/tinysdlc/schedule"><img src="https://agentmods.dev/badge/skills/minh-tam-solution/tinysdlc/schedule/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/minh-tam-solution/tinysdlc/schedule"><img src="https://agentmods.dev/badge/skills/minh-tam-solution/tinysdlc/schedule.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00080 | $0.01164 |
| Opus 5 | $0.00040 | $0.00582 |
| Sonnet 5 | $0.00016 | $0.00233 |
| Haiku 4.5 | $0.00008 | $0.00116 |
Grade A, and why
schedule 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Schedule Skill
Manage cron-based scheduled tasks that deliver messages to the tinysdlc incoming queue. Each schedule fires at a cron interval and writes a routed message (@agent_id <task>) to queue/incoming/, where the queue processor picks it up and invokes the target agent.
Commands
Use the bundled CLI scripts/schedule.sh for all operations.
Create a schedule
scripts/schedule.sh create \
--cron "EXPR" \
--agent AGENT_ID \
--message "Task context for the agent" \
[--channel CHANNEL] \
[--sender SENDER] \
[--label LABEL]
--cron— 5-field cron expression (required). Examples:"0 9 * * *"(daily 9am),"*/30 * * * *"(every 30 min),"0 0 * * 1"(weekly Monday midnight).--agent— Target agent ID (required). Must match an agent configured in settings.json.--message— The task context / prompt sent to the agent (required).--channel— Channel name in the queue message (default:schedule).--sender— Sender name in the queue message (default:Scheduler).--label— Unique label to identify this schedule (default: auto-generated). Use a descriptive label for easy management.
List schedules
scripts/schedule.sh list [--agent AGENT_ID]
Lists all tinysdlc schedules. Optionally filter by --agent to show only schedules targeting a specific agent.
Delete a schedule
scripts/schedule.sh delete --label LABEL
scripts/schedule.sh delete --all
Delete a specific schedule by label, or delete all tinysdlc schedules.
Workflow
- Confirm the target agent ID exists (check
settings.jsonor ask the user). - Determine the cron expression from the user's description (e.g., "every morning" →
"0 9 * * *"). - Compose a clear task message — this is the prompt the agent will receive.
- Run
scripts/schedule.sh createwith the parameters. - Verify with
scripts/schedule.sh list.
Cron expression quick reference
┌───────────── minute (0-59)
│ ┌───────────── hour (0-23)
│ │ ┌───────────── day of month (1-31)
│ │ │ ┌───────────── month (1-12)
│ │ │ │ ┌───────────── day of week (0-7, 0 and 7 = Sunday)
│ │ │ │ │
* * * * *
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 136 lines · 80 tokens per session scan A fdd80b2f1800
schedule is a skill published in the GitHub repository Minh-Tam-Solution/tinysdlc (10 stars, last pushed 6mo ago), licensed MIT. It adds 80 tokens to every session and 1,164 once invoked, about $0.0004 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 2026-08-31.
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