Skill 詳細

pulse

Recency and sentiment research can support investment research, but it is not equity-specific.

一致度一致の可能性株式リサーチ 向けにレビュー済み
出典alirezarezvani/claude-skills外部ソース
報告インストール数報告なし人気度の参考値

使用前に確認

自動レビューは関連性のみを確認し、安全性や推奨を保証しません。使用前に出典の説明を読んでください。

保存された出典プレビュー

SKILL.md

これはレビュー時に保存された抜粋です。完全で最新の内容は外部ソースを確認してください。

---
name: pulse
description: "Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis."
license: MIT
metadata:
  source_spec: "megaprompts/01-pulse-megaprompt.md"
  build_pattern: "Path B (direct conversion)"
  research_pack_convention: "Agent Integrity Rules block preserved verbatim per PR #657 audit"
  version: 1.0.0
---

# Pulse — Multi-Source Recency Research

> **Portability:** Works in both Claude Code CLI and Claude.ai. The optional X/Twitter phase requires browser automation and is skipped automatically if unavailable.

A recency-oriented research skill that synthesizes what people are saying about a topic across Reddit, Hacker News, the open web, and (optionally) X/Twitter — within a configurable time window. Output is a single coherent briefing with citations, engagement signals, and cross-platform pattern analysis. The skill captures the **current conversation**, not the canonical reference.

## Invocation

**Explicit trigger phrases:**
- "pulse on [topic]"
- "what's happening with [topic]"
- "what are people saying about [topic]"
- "current conversation about [topic]"
- "take the pulse of [topic]"
- "trending: [topic]"
- "find me info on [topic]"

Also covers: competitor research with recency flavor, trend discovery, tool comparisons, audience sentiment analysis.

## Agent Integrity Rules (Research-Pack Convention)

The following rules apply throughout the run. They are inherited from the research-pack convention and locked down by PR #657's cross-skill consistency audit.

- **Execution discipline.** Phases 1–3 run in parallel (Reddit + HN + Web are independent). Within each phase, sequential calls only. **1 q/sec rate limit per platform.** Confirm response received before next call within the same phase.
- **Source discipline.** Cite only sources returned by **this session's tool calls.** Training knowledge is labeled `[Background — not from search]` and excluded from primary findings count.
- **Three-count tracking.** Queries sent / sources received (shown) / sources cited. Surfaced in the audit log inline in the synthesis section. Use `scripts/citation_tracker.py` for the deterministic count.
- **Retry policy.** On failure → wait 3s → retry once → log. After **3 consecutive failures across all sources:** stop, alert user, share what was collected. Never deliver an empty file.
- **Plan-tier detection.** Reddit + HN are unauthenticated public JSON APIs (rate-limited per IP, not per plan). Surface rate-limit signals from response headers when available; degrade gracefully otherwise.

See `references/research_pack_conventions.md` for the canon and `references/parallel_execution_discipline.md` for the rate-limit rationale.

## Phase 0: Grill-Me Intake (2–4 forcing questions, one at a time)

Dependency-ordered. Each question carries explicit "why I'm asking". Stop condition: max 4.

### Q1 (root) — Topic Specificity

> **What's the topic? State it in 1–2 sentences — be specific. "AI" or "tech" will get you a vague survey; "self-hosted LLM deployment for small teams" or "Claude Code adoption among enterprise engineering orgs" will get you a useful answer.**
>
> *Why I'm asking:* Specificity dictates search quality. Vague topics produce vague briefings. If y
GitHub で全文を読む (外部ページ)
関連情報

関連する仕事