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 Stijnman/grok-custom-skills --skill whatsapp-message-ratergit clone --depth 1 https://github.com/Stijnman/grok-custom-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/stijnman/grok-custom-skills/whatsapp-message-rater)<a href="https://agentmods.dev/skills/stijnman/grok-custom-skills/whatsapp-message-rater"><img src="https://agentmods.dev/badge/skills/stijnman/grok-custom-skills/whatsapp-message-rater/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/stijnman/grok-custom-skills/whatsapp-message-rater"><img src="https://agentmods.dev/badge/skills/stijnman/grok-custom-skills/whatsapp-message-rater.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00042 | $0.00391 |
| Opus 5 | $0.00021 | $0.00196 |
| Sonnet 5 | $0.00008 | $0.00078 |
| Haiku 4.5 | $0.00004 | $0.00039 |
Grade A, and why
whatsapp-message-rater 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 9d 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.
What it actually says
WhatsApp Message Rater
When to Use
- User says rate this WhatsApp or task matches this capability
- User says analyze chat sentiment or task matches this capability
- User says score message urgency or task matches this capability
Workflow
- Parse message: sender, text, timestamp, attachments.
- Score sentiment (-1 to 1), urgency (0-10), spam (0-10).
- Output JSON summary plus one-line recommendation.
- Update per-contact profile if memory available.
Output Template
{"sentiment": 0.0, "urgency": 0, "spam": 0, "recommendation": ""}
Integrations
whatsapp-auto-responderprivacy-redactormulti-platform-messenger-bridge
Error Handling
| Failure | Response |
|---|---|
| Empty message | Return neutral scores; flag as no-content. |
| PII in message | Run privacy-redactor before storing profile. |
Gotchas
- Spam score > 7: never auto-reply; flag for user.
Example
Input: User request matching triggers above. Output: Structured result per workflow with integrations invoked as needed.
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.
- 9d ago First seen · 54 lines · 42 tokens per session scan A 364b27da33fd
whatsapp-message-rater is a skill published in the GitHub repository Stijnman/grok-custom-skills (9 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 391 once invoked, about $0.0002 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 2026-09-03.
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