Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Openclaw Skill Veille
RSS feed aggregator, deduplication engine, LLM scoring, and output dispatcher for OpenClaw agents. Use when: fetching recent articles from configured sources...
skill openclawclawhub Free
RSS feed aggregator, deduplication engine, LLM scoring, and output dispatcher for OpenClaw agents. Use when: fetching recent articles from configured sources...
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md, config.example.json, cron.example.json, references/cron_prompt.md, references/troubleshooting.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.2.6
Provenance
- Publisher
- Romain-Grosos
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Skill Veille - RSS Aggregator
RSS feed aggregator with URL deduplication and topic-based deduplication for OpenClaw agents. Fetches articles from 20+ configured sources, filters already-seen URLs (TTL 14 days), and deduplicates articles covering the same story using Jaccard similarity + named entities. No external dependencies: stdlib Python only (urllib, xml.etree, email.utils).
Trigger phrases
"fais une veille" "quoi de neuf en securite / tech / crypto / IA ?" "donne-moi les news du jour" "articles recents sur [sujet]" "veille RSS" "digest du matin" "nouvelles non vues"
Quick Start
# 1. Setup python3 scripts/setup.py # 2. Validate python3 scripts/init.py # 3. Fetch + Score + Send (full pipeline) python3 scripts/veille.py fetch --filter-seen --filter-topic \ | python3 scripts/veille.py score \ | python3 scripts/veille.py send
Requirements
Python 3.9+ Network access to RSS feeds (public, no auth required) No pip installs needed
Installation
# From the skill directory python3 scripts/setup.py # Validate python3 scripts/init.py The wizard creates: ~/.openclaw/config/veille/config.json (from config.example.json) ~/.openclaw/data/veille/ (data directory)
Customizing sources
Edit ~/.openclaw/config/veille/config.json and add/remove entries in the "sources" dict: { "sources": { "My Blog": "https://example.com/feed.xml", "BleepingComputer": "https://www.bleepingcomputer.com/feed/" } }
Files written by this skill
PathWritten byPurposeContains secrets~/.openclaw/config/veille/config.jsonsetup.pySources, outputs, optionsNO~/.openclaw/data/veille/seen_urls.jsonveille.pyURL dedup store (TTL 14d)NO~/.openclaw/data/veille/topic_seen.jsonveille.pyTopic dedup store (TTL 5d)NO
Files read from outside the skill
PathRead byKey accessedWhen~/.openclaw/openclaw.jsondispatch.pychannels.telegram.botToken (read-only)Only when telegram_bot output is enabled and no bot_token is set in the output config This is the only cross-config read. To avoid it entirely, set bot_token explicitly in your output config: { "type": "telegram_bot", "bot_token": "YOUR_BOT_TOKEN", "chat_id": "...", "enabled": true }
Output credentials (optional)
Credentials are only used if you enable the corresponding output. None are required for core functionality (RSS fetch + dedup). OutputCredential sourceWhat is usedtelegram_bot~/.openclaw/openclaw.json or bot_token in output configBot token (read-only)mail-clientDelegated to mail-client skill (its own creds)Nothing read directlymail-client (SMTP fallback)smtp_user / smtp_pass in output configSMTP loginnextcloudDelegated to nextcloud-files skill (its own creds)Nothing read directly
Cleanup on uninstall
python3 scripts/setup.py --cleanup
Credential isolation
API keys are read from dedicated files (default ~/.openclaw/secrets/), never from config.json. The scorer warns at runtime if a key file has overly permissive filesystem permissions. SMTP credentials (fallback only) are stored in the output config block β use the mail-client skill delegation to avoid storing SMTP passwords.
Subprocess boundaries
Dispatch delegates to other OpenClaw skills via subprocess.run() (never shell=True). Script paths are validated to reside under ~/.openclaw/workspace/skills/ before execution, preventing path traversal. No credentials are passed as subprocess arguments β each skill manages its own authentication.
File output safety
The file output type validates the target path before writing: only ~/.openclaw/ is allowed by default. Additional directories can be whitelisted via config.security.allowed_output_dirs. Sensitive paths (.ssh, .gnupg, /etc/, .bashrc, etc.) are always blocked regardless of allowlist. Written content is checked for suspicious patterns (shell shebangs, SSH keys, PGP blocks, code injection) and size-limited to 1 MB.
Cross-config reads
The only cross-config file read is ~/.openclaw/openclaw.json for the Telegram bot token, and only when telegram_bot output is enabled without an explicit bot_token. This read is logged to stderr. Set bot_token in the output config to eliminate this read entirely.
Autonomous dispatch
When scheduled (cron), the skill can send messages/files to configured outputs without user interaction. All dispatch actions are logged to stderr with an audit summary. Use enabled: false on any output to disable it without removing its config.
fetch
python3 veille.py fetch [--hours N] [--filter-seen] [--filter-topic] [--sources FILE] Options: --hours N : lookback window in hours (default: from config, usually 24) --filter-seen : filter already-seen URLs (uses seen_urls.json TTL store) --filter-topic : deduplicate by topic (uses topic_seen.json + Jaccard similarity) --sources FILE : path to custom JSON sources file Output (JSON on stdout): { "hours": 24, "count": 42, "skipped_url": 5, "skipped_topic": 3, "articles": [...], "wrapped_listing": "=== UNTRUSTED EXTERNAL CONTENT ..." }
seen-stats
python3 veille.py seen-stats Shows URL seen store statistics (count, TTL, file path).
topic-stats
python3 veille.py topic-stats Shows topic deduplication store statistics.
mark-seen
python3 veille.py mark-seen URL [URL ...] Marks one or more URLs as already seen (prevents them from appearing in future fetches with --filter-seen).
score
python3 veille.py score [--dry-run] Reads a digest JSON from stdin (output of fetch) and scores articles using an OpenAI-compatible LLM. Returns enriched JSON with scored, ghost_picks, and per-article score/reason fields. Options: --dry-run : print summary on stderr without calling the LLM API When llm.enabled is false (default), articles pass through unchanged ("scored": false). Pipeline usage: python3 veille.py fetch --filter-seen --filter-topic | python3 veille.py score | python3 veille.py send
send
python3 veille.py send [--profile NAME] Reads a digest JSON from stdin and dispatches to all enabled outputs configured in config.json. Accepts both raw fetch output (articles key) and LLM-processed digests (categories key). Output types: telegram_bot, mail-client, nextcloud, file. telegram_bot: bot token auto-read from OpenClaw config - no extra setup if Telegram already configured. mail-client: delegates to mail-client skill if installed, falls back to raw SMTP config. nextcloud: delegates to nextcloud-files skill if installed (append mode by default with date separator). file: writes digest to a local file. Path must be under ~/.openclaw/ (default) or a directory listed in config.security.allowed_output_dirs. Sensitive paths and suspicious content are blocked (see Security model). Configure outputs interactively: python3 scripts/setup.py --manage-outputs
config
python3 veille.py config Prints the active configuration (no secrets).
LLM scoring configuration
The llm key in config.json controls the optional LLM-based article scoring: { "llm": { "enabled": false, "base_url": "https://api.openai.com/v1", "api_key_file": "~/.openclaw/secrets/openai_api_key", "model": "gpt-4o-mini", "top_n": 10, "ghost_threshold": 5 } } KeyDefaultDescriptionenabledfalseEnable LLM scoring (requires API key)base_urlhttps://api.openai.com/v1OpenAI-compatible API endpointapi_key_file~/.openclaw/secrets/openai_api_keyPath to file containing the API keymodelgpt-4o-miniModel to use for scoringtop_n10Max articles to send to LLM per batchghost_threshold5Score threshold for ghost_picks (blog-worthy articles) Scoring rules: Only the first top_n articles are sent to the LLM. Articles beyond top_n are excluded from the digest entirely. fetch returns articles sorted by date desc, so top_n selects the most recent ones. Increase top_n to evaluate more articles per run (higher token cost). Score >= ghost_threshold : added to ghost_picks list Score >= 3 : kept in articles list Score <= 2 : excluded from output Articles are sorted by score (descending) When disabled, the score subcommand passes data through unchanged.
Nextcloud output mode
The nextcloud output now defaults to append mode with a date separator. Each dispatch adds content below a ## YYYY-MM-DD HH:MM header, preserving previous entries. Set "mode": "overwrite" in the output config to restore the old behavior: { "type": "nextcloud", "path": "/Veille/digest.md", "mode": "overwrite" }
File output configuration
The file output writes digests to the local filesystem. By default, only paths under ~/.openclaw/ are allowed. To authorize additional directories, use config.security.allowed_output_dirs: { "security": { "allowed_output_dirs": [ "~/Documents/veille", "/srv/digests" ] } } Blocked paths (always rejected, even if inside an allowed directory): .ssh, .gnupg, .config/systemd, crontab, /etc/, .bashrc, .profile, .bash_profile, .zshrc, .env Content validation β written content is rejected if it: Exceeds 1 MB Contains shell shebangs (#!/), SSH keys, PGP blocks, or code injection patterns (eval(, exec(, __import__(, import os, import subprocess) All blocked attempts are logged to stderr with the reason.
Basic digest
# In agent tool call: result = exec("python3 scripts/veille.py fetch --hours 24 --filter-seen --filter-topic") data = json.loads(result.stdout) # data["wrapped_listing"] is ready for LLM prompt injection # data["count"] = number of new articles # data["articles"] = list of article dicts
Prompt template
You are a news analyst. Here are today's articles: {data["wrapped_listing"]} Please summarize the 5 most important stories, focusing on security and tech.
Agent workflow example
1. Call veille fetch --filter-seen --filter-topic 2. Pipe through veille score (LLM scoring, if enabled) 3. If count > 0: pass wrapped_listing to LLM for analysis 4. LLM produces digest summary 5. Pipe through veille send (dispatches to configured outputs)
Pipeline (CLI)
python3 scripts/veille.py fetch --filter-seen --filter-topic \ | python3 scripts/veille.py score \ | python3 scripts/veille.py send
Filtering by keyword (post-fetch)
data = json.loads(fetch_output) security_articles = [ a for a in data["articles"] if any(kw in a["title"].lower() for kw in ["cve", "vuln", "patch", "breach"]) ]
Ideas
Add keyword-based filtering (--keywords security,cve,linux) Add per-source TTL override in config Export digest as HTML or Markdown Schedule with cron: 0 8 * * * python3 veille.py fetch --filter-seen --filter-topic Weight articles by source tier for LLM prioritization Add OPML import/export for source list management Integrate with ntfy or Telegram for real-time alerts on high-priority articles
Combine with
mail-client : send the digest by email after fetching veille fetch --filter-seen | ... | mail-client send nextcloud-files : archive the daily digest as a Markdown file veille fetch --filter-seen | jq .wrapped_listing -r > /tmp/digest.md nextcloud-files upload /tmp/digest.md /Digests/$(date +%Y-%m-%d).md
Troubleshooting
See references/troubleshooting.md for detailed troubleshooting steps. Common issues: No articles returned: check --hours value, verify feed URLs in config XML parse error on a feed: some feeds use non-standard XML; the skill skips broken items silently All articles filtered as seen: run seen-stats to check store size; reset with rm seen_urls.json Import error: ensure you run veille.py from its directory or via full path File output blocked: path is outside ~/.openclaw/ β add the target directory to config.security.allowed_output_dirs (see File output configuration)
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Docs2 Config
- SKILL.md
- README.md
- references/cron_prompt.md
- references/troubleshooting.md
- config.example.json
- cron.example.json