Ilia Alshanetsky
d7bff81757
* chore: fix YAML error in argument-hint * add codex auth support to responses API * Use gpt-5.1-codex-mini as default model for Codex auth Add CODEX_FALLBACK_MODELS chain (gpt-5.1-codex-mini → gpt-5.2) for Codex endpoint which doesn't support standard OpenAI models like gpt-4o-mini. Adds model fallback retry on 400 errors in the Codex search path. Also adds test_codex_auth.py with 22 unit tests covering JWT decoding, auth resolution, SSE parsing, and payload building. * Pass .env credentials to Bird Node subprocesses for X auth On platforms without browser cookie access (e.g. WSL2), Bird's vendored Node.js module cannot read AUTH_TOKEN/CT0 from Firefox or Chrome cookie stores. The .env config file already supports these values, but they were only loaded into the Python config dict — never exported to the environment of Node subprocesses. - Add AUTH_TOKEN/CT0 to env.py config key loading - Add set_credentials()/\_subprocess_env() to bird_x.py to inject credentials into the env dict passed to subprocess.run/Popen - Call set_credentials() in main() before Bird auth detection --------- Co-authored-by: Justin Williams <jblwilliams@gmail.com>
78 lines
3.3 KiB
Markdown
78 lines
3.3 KiB
Markdown
# last30days Skill Specification
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## Overview
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`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. OpenAI auth can come from `OPENAI_API_KEY` or Codex login credentials.
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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.
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## Architecture
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The orchestrator (`last30days.py`) coordinates discovery, enrichment, normalization, scoring, deduplication, and rendering. Each concern is isolated in `scripts/lib/`:
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- **env.py**: Load API keys from `~/.config/last30days/.env` and Codex auth from `~/.codex/auth.json`
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- **dates.py**: Date range calculation and confidence scoring
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- **cache.py**: 24-hour TTL caching keyed by topic + date range
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- **http.py**: stdlib-only HTTP client with retry logic
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- **models.py**: Auto-selection of OpenAI/xAI models with 7-day caching
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- **openai_reddit.py**: OpenAI Responses API + web_search for Reddit
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- **xai_x.py**: xAI Responses API + x_search for X
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- **reddit_enrich.py**: Fetch Reddit thread JSON for real engagement metrics
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- **hackernews.py**: Hacker News search via Algolia API (free, no auth)
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- **polymarket.py**: Polymarket prediction market search via Gamma API (free, no auth)
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- **normalize.py**: Convert raw API responses to canonical schema
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- **score.py**: Compute popularity-aware scores (relevance + recency + engagement)
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- **dedupe.py**: Near-duplicate detection via text similarity
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- **render.py**: Generate markdown and JSON outputs
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- **schema.py**: Type definitions and validation
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## Embedding in Other Skills
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Other skills can import the research context in several ways:
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### Inline Context Injection
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```markdown
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## Recent Research Context
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!python3 ~/.claude/skills/last30days/scripts/last30days.py "your topic" --emit=context
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```
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### Read from File
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```markdown
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## Research Context
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!cat ~/.local/share/last30days/out/last30days.context.md
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```
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### Get Path for Dynamic Loading
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```bash
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CONTEXT_PATH=$(python3 ~/.claude/skills/last30days/scripts/last30days.py "topic" --emit=path)
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cat "$CONTEXT_PATH"
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```
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### JSON for Programmatic Use
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```bash
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python3 ~/.claude/skills/last30days/scripts/last30days.py "topic" --emit=json > research.json
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```
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## CLI Reference
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```
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python3 ~/.claude/skills/last30days/scripts/last30days.py <topic> [options]
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Options:
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--refresh Bypass cache and fetch fresh data
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--mock Use fixtures instead of real API calls
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--emit=MODE Output mode: compact|json|md|context|path (default: compact)
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--sources=MODE Source selection: auto|reddit|x|both (default: auto)
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```
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## Output Files
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All outputs are written to `~/.local/share/last30days/out/`:
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- `report.md` - Human-readable full report
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- `report.json` - Normalized data with scores
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- `last30days.context.md` - Compact reusable snippet for other skills
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- `raw_openai.json` - Raw OpenAI API response
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- `raw_xai.json` - Raw xAI API response
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- `raw_reddit_threads_enriched.json` - Enriched Reddit thread data
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