# Research Scout

> Find new or contradictory external signals (web search, Reddit, Hacker News, Quora) and stage only validated learnings in memory/long-term-memory.md. Use when the user asks for new research, fresh strategies/tools announcements, or contradiction checks against existing docs.

- Skill: `talgacapri/research-scout` (Agent Skill)
- Install (CLI): `npx skillmds@latest add talgacapri/research-scout`
- Raw SKILL.md: https://api.skillmd.com/api/skills/talgacapri/research-scout/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: talgacapri (https://skillmd.com/u/talgacapri)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/talgacapri/research-scout

---


# Research Scout

Find new information that challenges or extends current project knowledge.

## Scope

This skill does one job:
1. Gather fresh signals from web search, Reddit, Hacker News, and Quora.
2. Cross-check against local docs so only novel or contradictory items survive.
3. Stage validated findings in `memory/long-term-memory.md` under `## new_learnings`.

## Commands

```bash
/research-scout run
/research-scout weekly-review
/research-scout status
```

- `run`: Execute the scout pipeline and append validated findings.
- `weekly-review`: Promote confirmed patterns and clear staging.
- `status`: Read current staged learnings and promoted patterns.

## Execution Rules

1. Use these source classes every run:
   - Web search (Google News RSS or equivalent search feed)
   - Reddit (search RSS)
   - Hacker News (Algolia API)
   - Quora (search constrained to quora.com)
2. Keep only findings that are either:
   - **New**: not already represented in local docs
   - **Contradictory**: challenge an existing assumption or prior guidance
3. Discard duplicates and low-signal items.
4. Each accepted finding must include:
   - Timestamp (UTC ISO)
   - Source URL
   - One-line note on what changed or was added

## Storage Contract

Write staged findings to:

- `memory/long-term-memory.md` → `## new_learnings`

Entry format:

```markdown
- [ ] 2026-04-25T18:00:00Z | source: https://example.com | note: Adds a new workflow for AI eval gating before rollout.
```

## Weekly Promotion Contract

Weekly review promotes repeated/confirmed patterns into:

- `memory/long-term-memory.md` → `## promoted_patterns`
- `context-library/pm-os-learning-log.md` → `## Research Scout Promoted Patterns`

After promotion, clear `## new_learnings` so it is a fresh staging queue.

## Automation

Run through GitHub workflows:

- `.github/workflows/research-scout-nightly.yml` (3x nightly)
- `.github/workflows/research-scout-weekly.yml` (weekly promotion + clear)

Core script:

- `scripts/research-scout/research_scout.py`