← Back to Skills Marketplace
danil4091

Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов.

by Danil4091 · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
866
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install vk-client-search-repetitor
Description
Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов.
Usage Guidance
This skill appears to do what it says, but exercise caution before installing: - Source verification: The skill's source/homepage is unknown. Prefer only installing skills from trusted authors or inspect files thoroughly. - Token handling: Do not reuse a high-privilege or personal account token. Create a dedicated VK service token with the minimal required scopes and store it securely (avoid committing it to plain config.json). - Config inconsistencies: The registry metadata omits required credentials while SKILL.md/config.json reference vk_service_token (README calls it access_token). Fix and verify where the token is expected before providing it. - Scraping vs API: SKILL.md allows HTML parsing as fallback. Scraping can violate site terms and may require cookies/extra permissions; prefer using VK API (wall.get) when possible. - Google Sheets mention: If the skill later asks to connect Google Sheets, that will require additional OAuth credentials — be cautious and review any additional prompts. - Scheduling and autonomy: The skill schedules checks every 3 hours and can run autonomously. If you want tighter control, run it manually or require user confirmation before each run. - Test safely: Run the skill in an isolated environment, with a throwaway/limited token and a small set of groups. Monitor network activity, logs, and the CSV output to confirm behavior. If you want, I can: (1) produce a checklist to sanitize the config and secure the token, (2) suggest a minimal VK token scope, or (3) draft a safer config file template that keeps secrets out of checked-in files.
Capability Analysis
Type: OpenClaw Skill Name: vk-client-search-repetitor Version: 1.0.0 The skill requires and handles a sensitive VK Service Token, performs network requests to VK, and writes collected data (including URLs) to the local file system. While these capabilities are plausibly needed for its stated purpose of finding leads, they represent high-risk operations. The instruction to 'парсинг HTML' (parse HTML) could lead to vulnerabilities depending on the agent's implementation, and saving external URLs to a CSV file (leads_math.csv) could pose risks if not handled securely downstream. No explicit malicious intent, such as data exfiltration to unauthorized endpoints or subversion of the agent via prompt injection, was found in the instructions or configuration.
Capability Assessment
Purpose & Capability
The skill's declared purpose (automated lead search in VK groups) aligns with the runtime instructions: it needs a VK service token, a list of target groups, internet access and file write access to save leads. However, registry metadata incorrectly lists no required environment variables/credentials while SKILL.md and config.json clearly require a VK API token (vk_service_token). The README also uses a different name ('access_token'), indicating sloppy metadata/config consistency.
Instruction Scope
SKILL.md stays within the stated purpose: fetch posts (via VK API or HTML parsing), filter by keywords, deduplicate, write CSV, and report. Potential concerns: HTML parsing is allowed as an alternative to API calls (this can lead to scraping behavior that may require extra permissions and is brittle), and 'optional Google Sheet' integration is mentioned without specifying how to authenticate — if the skill later requests Google credentials that would expand scope. The instructions ask to schedule repeating checks every 3 hours and to read/write local CSV files (expected for this task).
Install Mechanism
This is an instruction-only skill (no install spec, no code files to execute). That minimizes install-time risk—there is nothing being downloaded or executed automatically. Runtime will require network/file system access as declared in SKILL.md.
Credentials
The skill legitimately needs a VK service token and target group list. But the registry metadata claims no required credentials while SKILL.md/config.json require a VK token (vk_service_token). The token is expected to be stored in config.json (plaintext in the repo example), which is risky: storing service tokens unencrypted on disk increases exfiltration risk. The skill does not explicitly request unrelated credentials, but mentions optional Google Sheets without describing authentication — that would require additional credentials if used.
Persistence & Privilege
The skill does not request always: true and does not claim to modify other skills. It asks for schedule_task and filesystem/network access, which are consistent with periodic monitoring and saving CSVs. Autonomous invocation (default enabled) combined with internet + filesystem access raises the usual operational risk (an autonomous skill with credentials can act without each-time user approval), but that is expected for a monitor-style skill and not excessive by itself.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install vk-client-search-repetitor
  3. After installation, invoke the skill by name or use /vk-client-search-repetitor
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release: Automates the process of finding new math tutoring clients in VK groups with smart filtering and prioritization. - Monitors custom VK groups for new posts and comments seeking math tutors, filtering out ads from other tutors. - Prioritizes online tutoring requests and flags posts with high-value markers (e.g., ЕГЭ, олимпиада). - Saves structured leads with deduplication to CSV (or Google Sheets if configured). - Generates concise summary reports after each scan, with error handling for inaccessible groups or API rate limits. - Fully configurable: requires VK API token, group list, and output path.
Metadata
Slug vk-client-search-repetitor
Version 1.0.0
License
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов.?

Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов. It is an AI Agent Skill for Claude Code / OpenClaw, with 866 downloads so far.

How do I install Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов.?

Run "/install vk-client-search-repetitor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов. free?

Yes, Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов. is completely free (open-source). You can download, install and use it at no cost.

Which platforms does Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов. support?

Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов. is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Автоматический поиск клиентов (родителей) для репетитора по математике в группах ВКонтакте с умной фильтрацией и приоритизацией онлайн-запросов.?

It is built and maintained by Danil4091 (@danil4091); the current version is v1.0.0.

💬 Comments