PaperclipOrg
Claude Agent Skill · by Sickn33

Daily News Report

Install Daily News Report skill for Claude Code from sickn33/antigravity-awesome-skills.

Install
Terminal · npx
$npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill daily-news-report
Works with Paperclip

How Daily News Report fits into a Paperclip company.

Daily News Report drops into any Paperclip agent that handles this kind of work. Assign it to a specialist inside a pre-configured PaperclipOrg company and the skill becomes available on every heartbeat — no prompt engineering, no tool wiring.

S
SaaS FactoryPaired

Pre-configured AI company — 18 agents, 18 skills, one-time purchase.

$27$59
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Source file
SKILL.md358 lines
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---name: daily-news-reportdescription: "Scrapes content based on a preset URL list, filters high-quality technical information, and generates daily Markdown reports."risk: unknownsource: communitydate_added: "2026-02-27"--- # Daily News Report v3.0 > **Architecture Upgrade**: Main Agent Orchestration + SubAgent Execution + Browser Scraping + Smart Caching ## Core Architecture ```┌─────────────────────────────────────────────────────────────────────┐│                        Main Agent (Orchestrator)                    ││  Role: Scheduling, Monitoring, Evaluation, Decision, Aggregation    │├─────────────────────────────────────────────────────────────────────┤│                                                                      ││   ┌─────────────┐    ┌─────────────┐    ┌─────────────┐    ┌─────────────┐     ││   │ 1. Init     │ → │ 2. Dispatch │ → │ 3. Monitor  │ → │ 4. Evaluate │     ││   │ Read Config │    │ Assign Tasks│    │ Collect Res │    │ Filter/Sort │     ││   └─────────────┘    └─────────────┘    └─────────────┘    └─────────────┘     ││         │                  │                  │                  │           ││         ▼                  ▼                  ▼                  ▼           ││   ┌─────────────┐    ┌─────────────┐    ┌─────────────┐    ┌─────────────┐     ││   │ 5. Decision │ ← │ Enough 20?  │    │ 6. Generate │ → │ 7. Update   │     ││   │ Cont/Stop   │    │ Y/N         │    │ Report File │    │ Cache Stats │     ││   └─────────────┘    └─────────────┘    └─────────────┘    └─────────────┘     ││                                                                      │└──────────────────────────────────────────────────────────────────────┘         ↓ Dispatch                          ↑ Return Results┌─────────────────────────────────────────────────────────────────────┐│                        SubAgent Execution Layer                      │├─────────────────────────────────────────────────────────────────────┤│                                                                      ││   ┌─────────────┐   ┌─────────────┐   ┌─────────────┐              ││   │ Worker A    │   │ Worker B    │   │ Browser     │              ││   │ (WebFetch)  │   │ (WebFetch)  │   │ (Headless)  │              ││   │ Tier1 Batch │   │ Tier2 Batch │   │ JS Render   │              ││   └─────────────┘   └─────────────┘   └─────────────┘              ││         ↓                 ↓                 ↓                        ││   ┌─────────────────────────────────────────────────────────────┐   ││   │                    Structured Result Return                 │   ││   │  { status, data: [...], errors: [...], metadata: {...} }    │   ││   └─────────────────────────────────────────────────────────────┘   ││                                                                      │└─────────────────────────────────────────────────────────────────────┘``` ## Configuration Files This skill uses the following configuration files: | File | Purpose ||------|---------|| `sources.json` | Source configuration, priorities, scrape methods || `cache.json` | Cached data, historical stats, deduplication fingerprints | ## Execution Process Details ### Phase 1: Initialization ```yamlSteps:  1. Determine date (user argument or current date)  2. Read sources.json for source configurations  3. Read cache.json for historical data  4. Create output directory NewsReport/  5. Check if a partial report exists for today (append mode)``` ### Phase 2: Dispatch SubAgents **Strategy**: Parallel dispatch, batch execution, early stopping mechanism ```yamlWave 1 (Parallel):  - Worker A: Tier1 Batch A (HN, HuggingFace Papers)  - Worker B: Tier1 Batch B (OneUsefulThing, Paul Graham) Wait for results → Evaluate count If < 15 high-quality items:  Wave 2 (Parallel):    - Worker C: Tier2 Batch A (James Clear, FS Blog)    - Worker D: Tier2 Batch B (HackerNoon, Scott Young) If still < 20 items:  Wave 3 (Browser):    - Browser Worker: ProductHunt, Latent Space (Require JS rendering)``` ### Phase 3: SubAgent Task Format Task format received by each SubAgent: ```yamltask: fetch_and_extractsources:  - id: hn    url: https://news.ycombinator.com    extract: top_10  - id: hf_papers    url: https://huggingface.co/papers    extract: top_voted output_schema:  items:    - source_id: string      # Source Identifier      title: string          # Title      summary: string        # 2-4 sentence summary      key_points: string[]   # Max 3 key points      url: string            # Original URL      keywords: string[]     # Keywords      quality_score: 1-5     # Quality Score constraints:  filter: "Cutting-edge Tech/Deep Tech/Productivity/Practical Info"  exclude: "General Science/Marketing Puff/Overly Academic/Job Posts"  max_items_per_source: 10  skip_on_error: true return_format: JSON``` ### Phase 4: Main Agent Monitoring & Feedback Main Agent Responsibilities: ```yamlMonitoring:  - Check SubAgent return status (success/partial/failed)  - Count collected items  - Record success rate per source Feedback Loop:  - If a SubAgent fails, decide whether to retry or skip  - If a source fails persistently, mark as disabled  - Dynamically adjust source selection for subsequent batches Decision:  - Items >= 25 AND HighQuality >= 20 → Stop scraping  - Items < 15 → Continue to next batch  - All batches done but < 20 → Generate with available content (Quality over Quantity)``` ### Phase 5: Evaluation & Filtering ```yamlDeduplication:  - Exact URL match  - Title similarity (>80% considered duplicate)  - Check cache.json to avoid history duplicates Score Calibration:  - Unify scoring standards across SubAgents  - Adjust weights based on source credibility  - Bonus points for manually curated high-quality sources Sorting:  - Descending order by quality_score  - Sort by source priority if scores are equal  - Take Top 20``` ### Phase 6: Browser Scraping (MCP Chrome DevTools) For pages requiring JS rendering, use a headless browser: ```yamlProcess:  1. Call mcp__chrome-devtools__new_page to open page  2. Call mcp__chrome-devtools__wait_for to wait for content load  3. Call mcp__chrome-devtools__take_snapshot to get page structure  4. Parse snapshot to extract required content  5. Call mcp__chrome-devtools__close_page to close page Applicable Scenarios:  - ProductHunt (403 on WebFetch)  - Latent Space (Substack JS rendering)  - Other SPA applications``` ### Phase 7: Generate Report ```yamlOutput:  - Directory: NewsReport/  - Filename: YYYY-MM-DD-news-report.md  - Format: Standard Markdown Content Structure:  - Title + Date  - Statistical Summary (Source count, items collected)  - 20 High-Quality Items (Template based)  - Generation Info (Version, Timestamps)``` ### Phase 8: Update Cache ```yamlUpdate cache.json:  - last_run: Record this run info  - source_stats: Update stats per source  - url_cache: Add processed URLs  - content_hashes: Add content fingerprints  - article_history: Record included articles``` ## SubAgent Call Examples ### Using general-purpose Agent Since custom agents require session restart to be discovered, use general-purpose and inject worker prompts: ```Task Call:  subagent_type: general-purpose  model: haiku  prompt: |    You are a stateless execution unit. Only do the assigned task and return structured JSON.     Task: Scrape the following URLs and extract content     URLs:    - https://news.ycombinator.com (Extract Top 10)    - https://huggingface.co/papers (Extract top voted papers)     Output Format:    {      "status": "success" | "partial" | "failed",      "data": [        {          "source_id": "hn",          "title": "...",          "summary": "...",          "key_points": ["...", "...", "..."],          "url": "...",          "keywords": ["...", "..."],          "quality_score": 4        }      ],      "errors": [],      "metadata": { "processed": 2, "failed": 0 }    }     Filter Criteria:    - Keep: Cutting-edge Tech/Deep Tech/Productivity/Practical Info    - Exclude: General Science/Marketing Puff/Overly Academic/Job Posts     Return JSON directly, no explanation.``` ### Using worker Agent (Requires session restart) ```Task Call:  subagent_type: worker  prompt: |    task: fetch_and_extract    input:      urls:        - https://news.ycombinator.com        - https://huggingface.co/papers    output_schema:      - source_id: string      - title: string      - summary: string      - key_points: string[]      - url: string      - keywords: string[]      - quality_score: 1-5    constraints:      filter: Cutting-edge Tech/Deep Tech/Productivity/Practical Info      exclude: General Science/Marketing Puff/Overly Academic``` ## Output Template ```markdown# Daily News Report (YYYY-MM-DD) > Curated from N sources today, containing 20 high-quality items> Generation Time: X min | Version: v3.0>> **Warning**: Sub-agent 'worker' not detected. Running in generic mode (Serial Execution). Performance might be degraded. --- ## 1. Title - **Summary**: 2-4 lines overview- **Key Points**:  1. Point one  2. Point two  3. Point three- **Source**: Link- **Keywords**: `keyword1` `keyword2` `keyword3`- **Score**: ⭐⭐⭐⭐⭐ (5/5) --- ## 2. Title... --- *Generated by Daily News Report v3.0**Sources: HN, HuggingFace, OneUsefulThing, ...*``` ## Constraints & Principles 1.  **Quality over Quantity**: Low-quality content does not enter the report.2.  **Early Stop**: Stop scraping once 20 high-quality items are reached.3.  **Parallel First**: SubAgents in the same batch execute in parallel.4.  **Fault Tolerance**: Failure of a single source does not affect the whole process.5.  **Cache Reuse**: Avoid re-scraping the same content.6.  **Main Agent Control**: All decisions are made by the Main Agent.7.  **Fallback Awareness**: Detect sub-agent availability, gracefully degrade if unavailable. ## Expected Performance | Scenario | Expected Time | Note ||---|---|---|| Optimal | ~2 mins | Tier1 sufficient, no browser needed || Normal | ~3-4 mins | Requires Tier2 supplement || Browser Needed | ~5-6 mins | Includes JS rendered pages | ## Error Handling | Error Type | Handling ||---|---|| SubAgent Timeout | Log error, continue to next || Source 403/404 | Mark disabled, update sources.json || Extraction Failed | Return raw content, Main Agent decides || Browser Crash | Skip source, log entry | ## Compatibility & Fallback To ensure usability across different Agent environments, the following checks must be performed: 1.  **Environment Check**:    -   In Phase 1 initialization, attempt to detect if `worker` sub-agent exists.    -   If not exists (or plugin not installed), automatically switch to **Serial Execution Mode**. 2.  **Serial Execution Mode**:    -   Do not use parallel block.    -   Main Agent executes scraping tasks for each source sequentially.    -   Slower, but guarantees basic functionality. 3.  **User Alert**:    -   MUST include a clear warning in the generated report header indicating the current degraded mode. ## When to UseThis skill is applicable to execute the workflow or actions described in the overview.