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 agentmods add skills/suyoumo/clawprobench/routine-advisornpx skills add suyoumo/ClawProBench --skill routine-advisorgit clone --depth 1 https://github.com/suyoumo/ClawProBenchWrote 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/suyoumo/clawprobench/routine-advisor)<a href="https://agentmods.dev/skills/suyoumo/clawprobench/routine-advisor"><img src="https://agentmods.dev/badge/skills/suyoumo/clawprobench/routine-advisor.svg" alt="Measured on agentmods" 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 | $0.00019 | $0.01537 |
| Opus 5 | $0.00010 | $0.00768 |
| Sonnet 5 | $0.00004 | $0.00307 |
| Haiku 4.5 | $0.00002 | $0.00154 |
Grade A, and why
routine-advisor 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 4d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Routine Advisor
When the conversation suggests the user has a repeatable task or could benefit from automation, consider suggesting a routine.
When to Suggest
Suggest a routine when you notice:
- The user describes doing something repeatedly ("I check my PRs every morning")
- The user mentions forgetting recurring tasks ("I keep forgetting to...")
- The user asks you to do something that sounds periodic
- You've learned enough about the user to propose a relevant automation
- The user has installed extensions that enable new monitoring capabilities
Do not suggest or create a routine when the user asks for a one-time answer or says to do something now, right now, immediately, or ASAP without also asking for scheduling or recurrence.
How to Suggest
Be specific and concrete. Not "Want me to set up a routine?" but rather: "I noticed you review PRs every morning. Want me to create a daily 9am routine that checks your open PRs and sends you a summary?"
Always include:
- What the routine would do (specific action)
- When it would run (specific schedule in plain language)
- How it would notify them (which channel they're on)
Wait for the user to confirm before creating.
Pacing
- First 1-3 conversations: Do NOT suggest routines. Focus on helping and learning.
- After learning 2-3 user patterns: Suggest your first routine. Keep it simple.
- After 5+ conversations: Suggest more routines as patterns emerge.
- Never suggest more than 1 routine per conversation unless the user is clearly interested.
- If the user declines, wait at least 3 conversations before suggesting again.
Creating Routines
Use the builtin__trigger_create capability. Before creating, check builtin__trigger_list to avoid duplicates.
Parameters:
name: Short human-readable routine nameprompt: Clear, specific instruction for the full task each fire performs. Never tell the prompt to send results back to the requesting user — each fire's final reply is delivered automatically. "Send me the result" style asks are delivery routing, not a task step: satisfy them withdelivery_target_idalone, and never write a send-to-requester step into the prompt, even with the requester's own conversation ID pinned. When the task itself is to message someone else or post somewhere (for example "send Firat a joke every morning"), that belongs in the prompt: resolve the exact recipient conversation ID while creating the routine (while the user is present to confirm) and pin that ID in the prompt, so a fire never has to look a recipient up by name.delivery_target_id: Optional. Routes THIS routine's results to a specific outbound delivery target (an id frombuiltin__outbound_delivery_targets_list). Set it whenever the user names a destination for the routine's results; when omitted, results go to the user's default outbound delivery target at fire time.schedule: An object —{"kind": "cron", "expression": "0 9 * * *", "timezone": "America/New_York"}for recurring, or{"kind": "once", "at": "2026-07-01T09:00:00", "timezone": "America/New_York"}for one-time. The timezone is required (IANA name). Common cron schedules:- Daily 9am:
0 9 * * * - Weekday mornings:
0 9 * * MON-FRI - Weekly Monday:
0 9 * * MON - Every 2 hours during work:
0 9-17/2 * * MON-FRI - Sunday evening:
0 18 * * SUN
- Daily 9am:
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.
- 4d ago First seen · 125 lines · 19 tokens per session scan A 9e7ee9345003
routine-advisor is a skill published in the GitHub repository suyoumo/ClawProBench (823 stars, last pushed 9d ago), licensed Apache-2.0. It adds 19 tokens to every session and 1,537 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.
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