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Agent skill

Pulse

by alirezarezvani in alirezarezvani/claude-skills

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).

MITAuto-check passedMarketing & SEO

Install Pulse

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill pulse -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alirezarezvani/claude-skills pulse --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/research/pulse/skills/pulse .claude/skills/pulse && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
pulse
GitHub stars
28k
Token cost
~3.8k tokens
SKILL.md length
1,644 words
Files
7 (incl. scripts, references)
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

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).

  • Works in 5 steps: Grill-Me Intake (2–4 forcing questions,… → Reddit (parallel with HN + Web) → Hacker News (parallel with Reddit + Web) → …
  • The user requests multi-source recency intelligence on a topic (e.g.
  • SKILL.md covers Invocation, Agent Integrity Rules…, Phase 0: Grill-Me Intake (2–4… and Pre-flight, plus 10 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Pulse is an agent skill from alirezarezvani/claude-skills. 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…

Its SKILL.md is about 3.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/cross_platform_synthesis.md`, `references/parallel_execution_discipline.md` and `references/research_pack_conventions.md`).

It sits in Marketing & SEO, covering Competitor analysis, Market research and Customer feedback analysis. It works with Reddit and X (Twitter). The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • The user requests multi-source recency intelligence on a topic (e.g.
  • Pulse on [topic]
  • Whats happening with [topic]
  • What are people saying about [topic]

Example prompts

  • “pulse on [topic]”
  • “s happening with [topic]”
  • “what are people saying about [topic]”
  • “/pulse”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Grill-Me Intake (2–4 forcing questions, one at a time)
  2. Reddit (parallel with HN + Web)
  3. Hacker News (parallel with Reddit + Web)
  4. Web Search (parallel with Reddit + HN)
  5. X/Twitter (sequential, optional)

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Pulse loads about 3.8k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 210 tokens; SKILL.md has 1,644 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~210
When it runs · the whole SKILL.md, loaded when a task matches
~3.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~10k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 1,644 words, ~3,753 tokens.

Download SKILL.mdSave it as .claude/skills/pulse/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
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
metadata.build_pattern
Path B (direct conversion)
metadata.research_pack_convention
Agent Integrity Rules block preserved verbatim per PR #657 audit
metadata.version
1.0.0

Pulse — Multi-Source Recency Research

Portability: Works in Claude Code CLI and Claude.ai. Phase 4 accepts a local X/Twitter search export before trying a live interface.

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 your topic is broad, I'd rather narrow it now than spend a search budget on noise.

Refuse mush. If the user says "AI", push back once: "What about AI — adoption, safety, capability, regulation, or comparison? Pick an angle." If the user still won't narrow after one push-back, deliver with the explicit "vague topic — survey level, not depth" caveat.

Q2 (depends on Q1) — Angle

What angle matters most? Pick one:

  1. Trend — what's accelerating or decelerating
  2. Sentiment — what people feel about it
  3. Problems — pain points and complaints
  4. Opportunities — gaps and unmet needs
  5. Comparison — how it stacks up against alternatives

Why I'm asking: The angle dictates which sources weight more (Reddit for sentiment, HN for technical critique, Web for trend coverage) and how I rank the synthesis.

Forcing choice. Recommended default: trend, unless the topic obviously calls for a different angle.

Q3 (always) — Time Window

Time window: 7 / 14 / 30 / 60 / 90 days? Default is 30.

Why I'm asking: 7 days catches breaking conversation; 90 days catches sustained narrative shift. Pick based on how recent the news matters.

Forcing choice with default.

Q4 (depends on Q1) — Platform Scope

Any platform to skip? By default I'll cover Reddit + Hacker News + open web, plus X/Twitter if browser automation is available. Skip any you don't care about.

Why I'm asking: Skipping a platform saves search budget. Reddit dominates sentiment; HN dominates technical critique; Web dominates breadth; X dominates breaking conversation. Skip what doesn't fit your angle.

Asked only if Q1 + Q2 suggest some platforms are clearly off-target (e.g., consumer sentiment topic → HN less useful). Otherwise default to "all platforms".

Stop condition: After Q4 (or earlier with dependency skips), commit and start Phase 1. Max 4 questions, never bundle.

Pre-flight

Before any phase fires:

  1. Compute the time window with scripts/time_window_calculator.py --window <Nd>. Get back the Unix timestamp for created_at_i> (HN) and the t= parameter (hour|day|week|month|year|all) for Reddit.
  2. Generate the output slug with scripts/topic_slug_generator.py --topic "<topic>" --date $(date +%Y-%m-%d). Detect if ${RESEARCH_DIR}/pulse/<slug>-<date>.md already exists; if yes, append -v2 suffix or warn user.
  3. Start the three-count audit log with scripts/citation_tracker.py --action start --session pulse-<date>-<slug>. This file at ~/.pulse_sessions/<session>.json persists across the run.

Phase 1: Reddit (parallel with HN + Web)

API: reddit.com/search.json (unauthenticated, public JSON).

Queries (sequential within Reddit, 1 q/sec):

  1. sort=top&t=<window>&q=<topic> — top posts in window
  2. sort=new&t=<window>&q=<topic> — new posts in window (catches breaking signal)
  3. For each of the top 3–5 posts by score: fetch the comments JSON (<post-url>.json?limit=top) for the top 10–20 comments.

Headers / rate limits. Reddit rate-limits by IP, not plan. Throttle to 1 q/sec. If response has X-Ratelimit-Remaining: 0 or returns 429, wait 3s, retry once. If still failing, fall back to subreddit-restricted search (r/<topic-subreddit>/search.json) or ?raw_json=1.

Record each query: citation_tracker.py --action record_sent --session NAME --query "...". Record received counts: citation_tracker.py --action record_received --session NAME --count N.

Phase 2: Hacker News (parallel with Reddit + Web)

API: Algolia HN search (hn.algolia.com/api/v1/).

Queries (sequential within HN, 1 q/sec):

  1. search?query=<topic>&numericFilters=created_at_i><timestamp>&tags=story — stories in window
  2. search?query=<topic>&numericFilters=created_at_i><timestamp>&tags=comment — comments in window (catches discussion signal)

Failure handling. If HN returns empty: broaden the query (remove uncommon nouns); if still empty, drop the timestamp filter as last resort and label results "outside window".

HN bias note. HN skews technical / builder. Surface this in synthesis: "HN's voice is implementation-oriented; consumer sentiment will be under-represented here."

Phase 3: Web Search (parallel with Reddit + HN)

Tools: Available web search + fetch (e.g., WebSearch + WebFetch).

Query strategy (sequential within Web, 1 q/sec):

  1. Trusted publishers — "<topic>" site:nytimes.com OR site:wsj.com OR site:wired.com OR site:theverge.com OR site:techcrunch.com after:<date>
  2. Recent reviews — "<topic>" review <year> or "<topic>" "honest review" after:<date>
  3. Honest-opinion sources — "<topic>" problems OR complaints OR "worth it" after:<date>

Fetch the top 3–5 URLs per query. Truncate at the body, skip cookie/nav markup.

Citation discipline. Every claim in the Web section must trace to a fetched URL. Do NOT cite from snippets alone; fetch first.

Show full SKILL.md (635 more words)Show less

Phase 4: X/Twitter (sequential, optional)

Run last. Reasons:

  • Most likely to fail / require browser automation
  • X content overlaps significantly with Reddit/HN — so it adds delta, not primary signal

Interface (in priority order):

  1. User-provided JSON export. Import it before any live request:
    bash
    python3 scripts/citation_tracker.py \
  --action import_sources \
  --session NAME \
  --input /path/to/x-search.json \
  --platform x \
  --since 2026-07-01T00:00:00Z \
  --until 2026-08-01T00:00:00Z
    The importer accepts Xquik Tweet Search, X API v2, and generic JSON exports. It normalizes legacy and snake-case fields, joins X API includes.users, filters the requested window, and deduplicates by Tweet ID. It makes no network calls and requires no API key. The audit stores the filename and SHA-256 digest, not the user's absolute path.
  2. Grok if available in the harness.
  3. X API if authenticated.
  4. Browser automation if the harness supports it.
  5. Skip with note if none of the above are available.

Documented behavior:

If Phase 4 is skipped: include the section header ## X/Twitter with body Skipped — [reason: no browser automation / no Grok / no X API]. Do NOT pretend to have data.

Synthesis (Cross-Platform Patterns)

After Phases 1–4 complete (or Phase 4 skipped), produce the synthesis:

  1. Consensus signals — points where 3+ platforms agree (highest confidence). Tag each with cited source URLs.
  2. Controversy signals — points where platforms disagree. Note who says what.
  3. Pain points — recurring complaints across sources (esp. Reddit + Web).
  4. Excitement signals — recurring enthusiasm (esp. HN + X if available).
  5. Emerging trends — first-time mentions in newest posts but absent from older ones (compare sort=new vs sort=top).
  6. Gaps — what's notably absent that you'd expect to find.

For each pattern, cite the source URLs that support it. Use citation_tracker.py --action record_cited --session NAME --url "..." per citation.

See references/cross_platform_synthesis.md for detection heuristics.

Output

Save to file AND paste in chat:

File: ${RESEARCH_DIR}/pulse/<topic-slug>-<YYYY-MM-DD>.md (path from topic_slug_generator.py).

Format:

markdown
# [TOPIC] — Pulse (Last [N] Days)
*Generated: [DATE] | Angle: [Q2 choice]*

## TL;DR
[2-3 sentences max]

## Reddit
### Top Posts
- **[Title]** (r/sub) — [score, comments] — [summary] — [URL]
### What Reddit Is Saying
[Narrative paragraph]

## Hacker News
### Notable Stories
- **[Title]** — [points, comments] — [summary] — [URL]
### What HN Is Saying
[Narrative paragraph; note HN's technical/builder bias]

## Web
### Key Sources
- **[Title]** ([Publication]) — [takeaway] — [URL]
### What the Web Is Saying
[Narrative paragraph]

## X/Twitter (if available)
[Cleaned response, with handles/references preserved]
[Or: "Skipped — [reason]"]

## Cross-Platform Patterns
[Highest-confidence signals across sources]

## Key Takeaways
- [3-5 bullets]

## Content Angles (if applicable)
[2-3 specific angles supported by the data]

---
*Audit:* Queries sent: N (Reddit: a, HN: b, Web: c, X: d|skipped).
Sources received: M. Sources cited: K. Training knowledge: 0 ([Background] excluded from count).

Error Handling

FailureBehavior
Topic is too vague (Q1)Refuse to start. Re-ask Q1 once with examples. After 1 push-back, deliver with "vague topic" caveat.
Reddit blocks / rate-limitsTry ?raw_json=1 or fall back to subreddit-restricted search. Honor 3s-retry.
HN returns emptyBroaden query, drop timestamp filter as last resort, label results "outside window".
Web search returns nothing usefulNote in output; don't fabricate sources.
Browser automation unavailableImport a supplied export. Otherwise skip Phase 4 with a note.
Local X export is invalidStop Phase 4. Report the parse error. Do not guess missing records.
WebFetch times outUse what loaded, mark the source as "truncated".
3 consecutive failures across sourcesStop. Return what was collected with explicit "stopped early" note. Do NOT deliver empty file.
All sources failReturn error with diagnostic info. Do NOT deliver empty file.

Tooling

ScriptRole
scripts/time_window_calculator.pyCompute Unix timestamps + Reddit t= parameter from window string (30d, 7d, etc.). Deterministic from datetime.now().
scripts/citation_tracker.pyThree-count audit log plus local X export normalization and deduplication.
scripts/topic_slug_generator.pyFilesystem-safe slug + duplicate-date detection for output paths.

References

  • references/research_pack_conventions.md — Agent Integrity Rules canon (7+ sources: Google SRE, Reddit API docs, Algolia HN docs, exponential-backoff literature, citation discipline)
  • references/cross_platform_synthesis.md — consensus / controversy / pain detection across platforms (7+ sources)
  • references/parallel_execution_discipline.md — 1 q/sec rationale + plan-tier signals (7+ sources)

Anti-Patterns To Reject

  • Starting any search before the user commits to topic specificity (Q1)
  • Batching intake questions instead of one at a time
  • Hardcoded URLs that won't survive API changes (note format, explain may evolve)
  • Irrelevant person or brand references in the skill body
  • Tight coupling to one X/Twitter interface
  • Counting duplicate Tweet IDs or repeated citation URLs as separate sources
  • Missing fallback behavior on source failure
  • "Just use [specific tool]" without explaining what the tool does
  • Citing training knowledge in the cited count
  • Fabricating sources to fill out a section

Version: 1.0.0 Source spec: megaprompts/01-pulse-megaprompt.md (maintainer-local draft spec — gitignored, not present in the public repository) Build pattern: Path B (direct conversion). Re-grill with /cs:grill-with-docs if drift between spec and implementation surfaces.

© alirezarezvani, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in research/pulse/skills/pulse of alirezarezvani/claude-skills.

  • SKILL.md
  • references/cross_platform_synthesis.md
  • references/parallel_execution_discipline.md
  • references/research_pack_conventions.md
  • scripts/citation_tracker.py
  • scripts/time_window_calculator.py
  • scripts/topic_slug_generator.py

Open the folder on GitHubat commit 19392f7

Compare with similar skills

Pulse next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Pulse compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Pulse this skillalirezarezvani/claude-skills28k—~3.8kAutomated safety check: PassMIT
Reddit Competitor Analysis API Skillbrowser-act/skills6.1k2 repos~1.7kAutomated safety check: PassMIT
Competitor Launch Monitorunifapi-agent/agents587—~2.4kAutomated safety check: PassMIT
Company RadarVarnan-Tech/opendirectory674—~3.4kAutomated safety check: PassMIT
15 Social Listening Globalminhnv0807/ai-business-skills608—~4.8kAutomated safety check: PassMIT
Customer ResearchNexus-JPF/note-companion8706 repos~3.2kAutomated safety check: PassMIT

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Works with

Categories

Questions about Pulse

What does Pulse do?

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). Pulse is an agent skill from alirezarezvani/claude-skills. 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).

When should I use Pulse?

Pulse fits situations like: the user requests multi-source recency intelligence on a topic (e.g; pulse on [topic]; whats happening with [topic]; what are people saying about [topic].

How do I install Pulse in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill pulse -a claude-code`. Or copy the skill folder (research/pulse/skills/pulse in alirezarezvani/claude-skills) into .claude/skills/pulse in your project. Claude Code loads it when a task matches its description.

How do I install Pulse in Codex?

Run `npx skills add alirezarezvani/claude-skills --skill pulse -a codex`. Or copy the skill folder (research/pulse/skills/pulse in alirezarezvani/claude-skills) into .agents/skills/pulse in your project. Codex loads it when a task matches its description.

Can I use Pulse in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alirezarezvani/claude-skills --skill pulse -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pulse, .gemini/skills/pulse, .github/skills/pulse and .opencode/skills/pulse in your project.

What does Pulse need to run?

Going by SKILL.md and its folder, Pulse needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Pulse access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Pulse safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Pulse use?

Pulse is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Pulse use?

About 3.8k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 6.6k tokens, read only when the agent opens those files.

What are the alternatives to Pulse?

Skills that share tags, products or a category with Pulse: Reddit Competitor Analysis API Skill (browser-act/skills, 6.1k stars), Competitor Launch Monitor (unifapi-agent/agents, 587 stars), Company Radar (Varnan-Tech/opendirectory, 674 stars) and 15 Social Listening Global (minhnv0807/ai-business-skills, 608 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Pulse?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,829 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

Source: alirezarezvani/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.