pulse
Skill9 starsChanged 16 days agoMITView on GitHub
Community-pulse research on any topic — "what are people saying about X right now." Fans out parallel sub-agents across web search, Hacker News, Reddit, and GitHub; ranks findings by real engagement (points/upvotes/stars/comments); flags rumors; and writes a cited brief to chat plus saved .md and .html files. Use when the user wants the current community conversation / recent buzz / sentiment / "last 30 days" view on a person, product, project, or concept — e.g. "/pulse <topic>", "what's the buzz on X", "what are people saying about X lately", "research recent discussion on X". For exhaustive, adversarially fact-checked web reports, prefer the deep-research skill instead.
21 other projects use a version of this.
Adopted by
Most recently taken up by
- hemal08ce094/DesignSkillsSwiftUItheir own version, first seen Nov 8, 2026
- blamechris/chroxytheir own version, first seen Nov 8, 2026
- lsnackerman/raw-clauding-skillstheir own version, first seen Nov 1, 2026
- pendo-io/Product-Looptheir own version, first seen Nov 1, 2026
- bekhruztbx/ai-creative-teamtheir own version, first seen Oct 25, 2026
- simota/agent-skillstheir own version, first seen Oct 23, 2026
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Projects with it also use ant, artistic and 10 more.
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Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
bergsideSkillant
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Other versions21 projects use a version of this.
Word for word · 0
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Wrote their own version · 21
- bergside/awesome-design-skills★ 2.9ksame name
- Nunchi-trade/agent-cli★ 521same name
- simota/agent-skills★ 96same name
- lsnackerman/raw-clauding-skills★ 45same name
- bekhruztbx/ai-creative-team★ 18same name
- Hassaan146/claude-skills★ 18same name
- blamechris/chroxy★ 8same name
- linggen/skills★ 3same name
- wheslleyrimar/BuildCLI-Agents★ 3same name
- FeedbackPulseApp/hr-skills★ 2same name
11 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository21 other files it gives its agents.
The file
We split this skill into the rules it gives an agent
10 rules. 0 are common, 6 are distinctive, and 4 are very specific to this project.
0
Common
Most of the 18 edited versions we read keep these.
6
Distinctive
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 32
Run immediately for clear topics.
- Very specific: line 50
Do light entity resolution first when useful (e.g.
- Very specific: line 63
Use subagent_type: "Explore" (read-only, fast) for fetch-heavy sources.
- Very specific: line 74
Use WebSearch with several query variations (topic + "news"/"review"/"discussion"
- Distinctive: line 76
Authority over SEO: prefer primary sources (official posts, the actual thread/repo, named practitioners) over SEO-optimized aggregators and …
- Distinctive: line 115
If a source returns nothing usable after its fallback, record it as unreachable — do not fabricate.
- Very specific: line 120
Check for a previous pulse (delta memory): look for earlier out/pulse/<slug>-*.md files for this topic.
- Distinctive: line 143
If the user asked for ELI5, prepend a short plain-language summary above TL;DR.
- Distinctive: line 168
Keyless only: Never request or use API keys.
- Distinctive: line 169
No fabrication: Every claim → a real fetched source.
“Common” is measured: kept by at least 6 in 10 of the 18 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
pulse — community-pulse research
/pulse <topic> [window/flags in plain language]
Answer one question: what is the community actually saying about this topic right now, and what's resonating? You ground every claim in a real source and rank by real engagement — not by what a search engine's editors surfaced.
Inputs
- Topic (required): a person, product/company, project/repo, or concept/event.
- Window (optional, plain language): default last 30 days. Honor overrides like "last week", "past 6 months", "this year". Record the resolved window.
- Any other plain-language steering ("focus on Reddit", "ELI5", "just the drama").
Step 0 — Resolve scope (ask only if genuinely ambiguous)
Run immediately for clear topics. Ask 1–2 quick questions only if:
- the name maps to multiple plausible entities (e.g. a common name, an ambiguous product), or
- there's no obvious angle and the result would likely research the wrong thing.
Otherwise proceed and state your assumptions in the brief header.
Auto-detect the topic type and weight sources accordingly:
| Detected type | Source emphasis |
| Person (dev/tech) | GitHub (velocity) + Hacker News + web + Reddit |
| Person (non-tech) | Web + Reddit (skip/deprioritize GitHub) |
| Product / company | Reddit + web + Hacker News (GitHub if it's a tool) |
| Project / repo / tool | GitHub + Hacker News + Reddit + web |
| Concept / event | Web + Hacker News + Reddit (skip GitHub) |
Do light entity resolution first when useful (e.g. the canonical subreddit, the
GitHub owner/repo or username, the official site) so sub-agents search the right
handles rather than guessing.
Step 1 — Fan out: parallel source sub-agents
Spawn the relevant source sub-agents concurrently (one message, multiple Agent
calls). Skip sources the topic type deprioritizes. Give each the topic, resolved
entities, and the time window. Each sub-agent must return structured findings:
for every item — title, url, source, engagement (the raw metric + its kind),
date, and a 1–2 sentence snippet. Then it deepens its top 2–3 items
(below). Each gathers ~8–10 candidates before deepening.
Use subagent_type: "Explore" (read-only, fast) for fetch-heavy sources.
Effort scaling: match the fan-out to the ask. A niche topic or an explicit
"quick check" needs only the 2 best-matched sources from the table; the full
fan-out is for broad or clearly hot topics. Lossless hand-off: if a
sub-agent's deepened findings run long (many quotes/threads), have it write the
full extracts to out/pulse/.work/<source>.md and return just its ranked
summary — read the files at synthesis instead of losing detail in the relay.
Web sub-agent
- Use
WebSearchwith several query variations (topic + "news"/"review"/"discussion"- recency terms). Prefer results inside the window.
- Authority over SEO: prefer primary sources (official posts, the actual thread/repo, named practitioners) over SEO-optimized aggregators and listicle farms. A claim that appears only on low-quality aggregator sites is low-trust — mark it accordingly.
- Engagement proxy: publication prominence + how often a story recurs across results.
- Deepen top 2–3:
WebFetchthe article and extract the core claim + any quotes.
Hacker News sub-agent (free Algolia API — most reliable signal)
- Search:
WebFetch→https://hn.algolia.com/api/v1/search?query=<TOPIC>&tags=story&numericFilters=created_at_i>UNIX_START(computeUNIX_STARTwith a real shell command — e.g.date -d '30 days ago' +%s— never guess the timestamp; for relevance over recency use/searchinstead of/search_by_date). engagement=pointsandnum_comments.- Deepen top 2–3: fetch
https://hn.algolia.com/api/v1/items/<objectID>and pull the highest-signal top-level comments (the actual takes).
Reddit sub-agent (best-effort, keyless)
- Try
WebFetchon public JSON:https://www.reddit.com/search.json?q=<TOPIC>&sort=top&t=month(maptto the window:week/month/year), and/orhttps://www.reddit.com/r/<SUB>/search.json?...&restrict_sr=1. engagement=ups(upvotes) andnum_comments.- Deepen top 2–3: fetch the thread JSON (
<permalink>.json) and pull top comments. - Fallback chain on 403/empty: first retry the same JSON paths on
old.reddit.com(often served whenwwwis blocked); if that also fails, useWebSearchforsite:reddit.com <topic>andWebFetchthe threads. Note in the brief that Reddit was reached via fallback.
GitHub sub-agent (keyless REST, 60 req/hr)
- Repo/tool topic:
https://api.github.com/search/repositories?q=<TOPIC>&sort=stars, then for the chosen repo pull recentcommits,releases, and open/closed PR counts to gauge shipping velocity. - Person topic: resolve the username, then
users/<u>+ recentusers/<u>/events(public) to summarize what they're shipping. engagement= stars, recent commit/PR/release cadence.
If a source returns nothing usable after its fallback, record it as unreachable — do not fabricate.
Step 2 — Synthesize (main agent)
- Check for a previous pulse (delta memory): look for earlier
out/pulse/<slug>-*.mdfiles for this topic. If one exists, read the most recent one and compute the delta for a Since last pulse section: which clusters are new, which previous stories have faded, and which previously Disputed/Unconfirmed items have since been confirmed or debunked (say which, with a source). This is what makes repeat pulses on a tracked topic useful — the delta, not a second snapshot. Skip silently on the first run for a topic. - Dedup & cluster: merge the same story appearing across sources into one cluster; keep the strongest engagement signal and cite all sources in the cluster.
- Rank clusters by engagement (normalize across kinds — treat HN points, Reddit upvotes, GitHub stars, and comment volume as comparable "this resonated" signals; weight recency within the window).
- Flag reliability: explicitly tag rumors, speculation, single-source claims, and contested items as Disputed/Unconfirmed. Never let a rumor read as fact.
- Pull Best Takes: 2–5 genuinely notable/clever/viral quotes, each attributed with its source and engagement.
Step 3 — Emit the brief
Render the brief in chat per references/brief-template.md (read it when
you reach this step), then save it as .md and a self-contained .html file
(see Output files). Cite inline as ([source], <engagement>) with a linked URL.
If the user asked for ELI5, prepend a short plain-language summary above TL;DR.
Output files
Save to ./out/pulse/ in the current working directory:
out/pulse/<slug>-<YYYY-MM-DD>.md— the markdown brief verbatim.out/pulse/<slug>-<YYYY-MM-DD>.html— a bespoke, distinctively designed brief (see below). Self-contained: inline<style>, no JavaScript, links preserved, engagement metrics visible, responsive, print-friendly.
<slug> = topic lowercased, non-alphanumerics → hyphens. Compute the date with a
shell command (e.g. date +%F) — do not guess it. Create out/pulse/ if needed;
the briefs are the user's to commit or ignore — don't edit .gitignore for them.
Tell the user the two saved paths at the end.
Designing the HTML brief
Design the .html via the frontend-design skill using the brief in
references/html-design.md; if unavailable, fall back to a clean self-contained
dark-mode, no-JS layout.
Guardrails
- Keyless only. Never request or use API keys. Degrade gracefully.
- No fabrication. Every claim → a real fetched source. Mark unreachable sources honestly in the header.
- Recency discipline. Stay inside the window; if a pivotal item is older, include it but label it as background/older context.
- Engagement is the spine. Order by what resonated, show the numbers inline.
- Speed over exhaustiveness. This is a pulse, not a dossier — for the latter,
point to
deep-research.
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