feat: integrate last30days and daily-news-report skills

skills/last30days/SPEC.md

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+# last30days Skill Specification
+
+## Overview
+
+`last30days` is a Claude Code skill that researches a given topic across Reddit and X (Twitter) using the OpenAI Responses API and xAI Responses API respectively. It enforces a strict 30-day recency window, popularity-aware ranking, and produces actionable outputs including best practices, a prompt pack, and a reusable context snippet.
+
+The skill operates in three modes depending on available API keys: **reddit-only** (OpenAI key), **x-only** (xAI key), or **both** (full cross-validation). It uses automatic model selection to stay current with the latest models from both providers, with optional pinning for stability.
+
+## Architecture
+
+The orchestrator (`last30days.py`) coordinates discovery, enrichment, normalization, scoring, deduplication, and rendering. Each concern is isolated in `scripts/lib/`:
+
+- **env.py**: Load and validate API keys from `~/.config/last30days/.env`
+- **dates.py**: Date range calculation and confidence scoring
+- **cache.py**: 24-hour TTL caching keyed by topic + date range
+- **http.py**: stdlib-only HTTP client with retry logic
+- **models.py**: Auto-selection of OpenAI/xAI models with 7-day caching
+- **openai_reddit.py**: OpenAI Responses API + web_search for Reddit
+- **xai_x.py**: xAI Responses API + x_search for X
+- **reddit_enrich.py**: Fetch Reddit thread JSON for real engagement metrics
+- **normalize.py**: Convert raw API responses to canonical schema
+- **score.py**: Compute popularity-aware scores (relevance + recency + engagement)
+- **dedupe.py**: Near-duplicate detection via text similarity
+- **render.py**: Generate markdown and JSON outputs
+- **schema.py**: Type definitions and validation
+
+## Embedding in Other Skills
+
+Other skills can import the research context in several ways:
+
+### Inline Context Injection
+```markdown
+## Recent Research Context
+!python3 ~/.claude/skills/last30days/scripts/last30days.py "your topic" --emit=context
+```
+
+### Read from File
+```markdown
+## Research Context
+!cat ~/.local/share/last30days/out/last30days.context.md
+```
+
+### Get Path for Dynamic Loading
+```bash
+CONTEXT_PATH=$(python3 ~/.claude/skills/last30days/scripts/last30days.py "topic" --emit=path)
+cat "$CONTEXT_PATH"
+```
+
+### JSON for Programmatic Use
+```bash
+python3 ~/.claude/skills/last30days/scripts/last30days.py "topic" --emit=json > research.json
+```
+
+## CLI Reference
+
+```
+python3 ~/.claude/skills/last30days/scripts/last30days.py <topic> [options]
+
+Options:
+  --refresh           Bypass cache and fetch fresh data
+  --mock              Use fixtures instead of real API calls
+  --emit=MODE         Output mode: compact|json|md|context|path (default: compact)
+  --sources=MODE      Source selection: auto|reddit|x|both (default: auto)
+```
+
+## Output Files
+
+All outputs are written to `~/.local/share/last30days/out/`:
+
+- `report.md` - Human-readable full report
+- `report.json` - Normalized data with scores
+- `last30days.context.md` - Compact reusable snippet for other skills
+- `raw_openai.json` - Raw OpenAI API response
+- `raw_xai.json` - Raw xAI API response
+- `raw_reddit_threads_enriched.json` - Enriched Reddit thread data