Files

T

Ilia Alshanetsky d7bff81757 fix(bird_x): pass .env credentials to Node subprocesses for WSL2/headless auth

* 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>

2026-03-02 23:24:59 -08:00

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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. OpenAI auth can come from OPENAI_API_KEY or Codex login credentials.

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 API keys from ~/.config/last30days/.env and Codex auth from ~/.codex/auth.json
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
hackernews.py: Hacker News search via Algolia API (free, no auth)
polymarket.py: Polymarket prediction market search via Gamma API (free, no auth)
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

## Recent Research Context
!python3 ~/.claude/skills/last30days/scripts/last30days.py "your topic" --emit=context

Read from File

## Research Context
!cat ~/.local/share/last30days/out/last30days.context.md

Get Path for Dynamic Loading

CONTEXT_PATH=$(python3 ~/.claude/skills/last30days/scripts/last30days.py "topic" --emit=path)
cat "$CONTEXT_PATH"

JSON for Programmatic Use

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

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