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 GrizzlySMS-Git/grizzly-sms-mcp --skill grizzly-sms-skillgit clone --depth 1 https://github.com/GrizzlySMS-Git/grizzly-sms-mcpWrote 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/grizzlysms-git/grizzly-sms-mcp/grizzly-sms-skill)<a href="https://agentmods.dev/skills/grizzlysms-git/grizzly-sms-mcp/grizzly-sms-skill"><img src="https://agentmods.dev/badge/skills/grizzlysms-git/grizzly-sms-mcp/grizzly-sms-skill/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/grizzlysms-git/grizzly-sms-mcp/grizzly-sms-skill"><img src="https://agentmods.dev/badge/skills/grizzlysms-git/grizzly-sms-mcp/grizzly-sms-skill.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 | $0.00015 | $0.01244 |
| Opus 5 | $0.00008 | $0.00622 |
| Sonnet 5 | $0.00003 | $0.00249 |
| Haiku 4.5 | $0.00002 | $0.00124 |
Grade A, and why
grizzly_sms 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 12d 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.
This is a copy
88% identical to grizzly_sms — 21 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grizzly SMS Skill
Use this skill when the user needs: SMS verification, virtual numbers (Uber, Telegram, WhatsApp, Instagram, etc.), balance, prices, countries, services, or account registration with a rented phone number.
API Key — Ask in Dialog
Before running any Grizzly command, you MUST ask the user for the API key (unless they already gave it in this conversation):
Please provide your Grizzly SMS API key. Register on grizzlysms.com, then go to the API section (grizzlysms.com/docs) and copy the key.
When the user provides the key in chat — use it immediately. Pass it via exec env on every Grizzly call. Do NOT tell the user to set environment variables or edit config. The exec tool accepts env overrides; use them.
exec(command="node {baseDir}/scripts/grizzly-cli.mjs get_services", env={"GRIZZLY_SMS_API_KEY": "<exact_key_user_sent>"})
Example: user sends e069d36075b9b230fe1eb159b86526d1 → use env={"GRIZZLY_SMS_API_KEY": "e069d36075b9b230fe1eb159b86526d1"} in exec. Then proceed with get_services, request_number, etc.
If the key is already in config (skills.entries.grizzly_sms.env), omit env. Otherwise always ask and pass via env.
DO NOT ask the user to set GRIZZLY_SMS_API_KEY in environment variables or config files when they already provided the key in chat. Use it directly.
How to Call
There is NO tool named grizzly_sms.get_services(). You MUST use the exec tool. Example:
exec(command="node {baseDir}/scripts/grizzly-cli.mjs get_services", env={"GRIZZLY_SMS_API_KEY": "<user_key>"})
Use host=gateway only if tools.exec.host is configured for gateway. OpenClaw replaces {baseDir} with the skill folder path.
Commands (run via exec)
| What to do | Exec command |
|---|---|
| List services (find Uber) | node {baseDir}/scripts/grizzly-cli.mjs get_services |
| List countries (Brazil=73) | node {baseDir}/scripts/grizzly-cli.mjs get_countries |
| Check balance | node {baseDir}/scripts/grizzly-cli.mjs get_balance |
| Request number | node {baseDir}/scripts/grizzly-cli.mjs request_number ub 73 |
| Get SMS code | node {baseDir}/scripts/grizzly-cli.mjs get_status <activationId> |
| Complete activation | node {baseDir}/scripts/grizzly-cli.mjs set_status <activationId> 6 |
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.
- 12d ago First seen · 103 lines · 15 tokens per session scan A 1e0ef578a642
grizzly_sms is a skill published in the GitHub repository GrizzlySMS-Git/grizzly-sms-mcp (15 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 1,244 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to grizzly_sms, differing in 21 lines, and is treated as a copy.
Other skills, from other repositories
context-recovery
Recovers project handoff context from local Codex, Claude Code, Gemini, CodeBuddy, and codexmate-derived sessions. Use when the user asks what happened in prior project/PR/branch/file/error work, needs a handoff brief, wants old decisions or validations recovered, or asks to summarize cross-session project activity…
wecom-mcp-doc
A connection for working with WeCom documents and smart spreadsheets, including their content, columns, rows, and uploaded files. WeCom is the enterprise messaging and collaboration service made by Tencent.
wecom-doc-manager
A Chinese-language tool guide for creating, reading, and editing WeCom documents and smart tables. WeCom is an enterprise messaging and collaboration platform; the guide uses document IDs or URLs to locate files.
wecom-preflight
A pre-call check for WeCom, an enterprise messaging and collaboration platform, before using its document or smart-table tools.
approval
Approval workflow skill. View pending approval tasks and approve or reject service requests.
prometheus
Prometheus monitoring and alerting for cloud-native observability. Use when implementing metrics collection, PromQL queries, alerting rules, service discovery, recording rules, and scrape config.