last30days

last30days

Research recent evidence across social platforms, community forums, prediction markets, GitHub, and grounded web results, then merge everything into one brief.

When to use

• Use when you need a last-30-days research brief on a person, company, product, market, tool, or trend.
• Use when you want a recent competitor comparison, launch reaction summary, creator/community sentiment scan, or shipping update.
• Use when you want structured JSON with query_plan, ranked_candidates, clusters, and items_by_source.

When NOT to use

• Do not use for timeless encyclopedia questions with no recent evidence requirement.
• Do not use when you need only one official source and do not want social/community signals.

Capabilities

• AISA-hosted planning, reranking, synthesis, grounded web search, X/Twitter search, YouTube search, and Polymarket search.
• Public Reddit and Hacker News retrieval with fail-soft behavior.
• Official GitHub API search when GH_TOKEN or GITHUB_TOKEN is available.
• Hosted discovery for TikTok, Instagram, Threads, and Pinterest when enabled in runtime config.

Setup

• AISA_API_KEY is the main hosted credential.
• GH_TOKEN or GITHUB_TOKEN is optional for GitHub search only.
• Python 3.12+ is required.

for py in /usr/local/python3.12/bin/python3.12 python3.14 python3.13 python3.12 python3; do
  command -v "$py" >/dev/null 2>&1 || continue
  "$py" -c 'import sys; raise SystemExit(0 if sys.version_info >= (3, 12) else 1)' || continue
  LAST30DAYS_PYTHON="$py"
  break
done

Quick Reference

bash "${SKILL_ROOT}/scripts/run-last30days.sh" "$ARGUMENTS" --emit=compact
"${LAST30DAYS_PYTHON}" "${SKILL_ROOT}/scripts/last30days.py" "$ARGUMENTS" --emit=json
"${LAST30DAYS_PYTHON}" "${SKILL_ROOT}/scripts/last30days.py" "$ARGUMENTS" --quick
"${LAST30DAYS_PYTHON}" "${SKILL_ROOT}/scripts/last30days.py" "$ARGUMENTS" --deep
"${LAST30DAYS_PYTHON}" "${SKILL_ROOT}/scripts/last30days.py" "$ARGUMENTS" --search=reddit,x,grounding
"${LAST30DAYS_PYTHON}" "${SKILL_ROOT}/scripts/last30days.py" --diagnose

Inputs And Outputs

• Input: a topic or comparison query such as OpenAI Agents SDK, OpenClaw vs Codex, or Peter Steinberger.
• Output: synthesized research plus provider_runtime, query_plan, ranked_candidates, clusters, and items_by_source.

Example Queries

• last30days OpenAI Agents SDK
• last30days Peter Steinberger
• last30days OpenClaw vs Codex
• last30days Kanye West --quick