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Whathappened

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kunchenguid
whathappened

Brief what just happened on a topic and map public opinion from X (Twitter) only. Adaptive recency window biased to the freshest coherent story. Soft exception: at most one web lookup for entity resolution. Use when the user runs /whathappened, or asks what happened / what's going on / X or Twitter reaction / public opinion on X about a person, product, launch, or event. Grok Build only (requires native X tools). Neutral analyst tone. No discovery mode in v1.

Overview

Publisherkunchenguid
Repositorywhathappened
Skill namewhathappened
Stars
232
Forks
17
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by kunchenguid on GitHub. Read the source before you install it.

Installation

Install the Whathappened AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/kunchenguid/whathappened/tree/main/skills/whathappened
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/kunchenguid/whathappened.git /tmp/whathappened
mkdir -p .claude/skills
cp -r /tmp/whathappened/skills/whathappened .claude/skills/whathappened
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Whathappened in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Whathappened on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Whathappened is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

/whathappened

You are running the whathappened skill. Produce a neutral briefing of what happened and what public X is saying about a named topic.

This is not generic research. Follow this file top to bottom.

Host requirement

You need these tools:

  • x_keyword_search
  • x_semantic_search
  • x_thread_fetch
  • x_user_search

If they are missing, stop. Tell the user this skill only works in Grok Build (or another host with those X tools). Do not fake an X briefing from web search.

Hard rules

  1. X-first synthesis. All claims about the event and public opinion come from X tool results. Never invent posts, handles, engagement, or quotes.
  2. Soft web exception. At most one web lookup (web_search or web_fetch) only to resolve what/who the topic is (official name, handle, product identity). Do not use web for opinions, sentiment, or "what people think." If you use the web lookup, say so in Gaps.
  3. No discovery. If the user gives no topic, or asks "what's trending / what's hot on X," do not invent a feed. Ask for a topic in one short question.
  4. No flags in v1. Ignore or gently ignore flag-like tokens (--deep, window overrides). Infer window from the pulse (below).
  5. Neutral analyst tone. No hype voice, no dunking, no "the room is screaming." Report camps and debates as observed.
  6. Adaptive window, freshest-first. Do not default to 30 days. Prefer the shortest window that still explains the story.
  7. Opinion is not ground truth. Frame sentiment as public conversation on this X sample.
  8. Citations. Prefer @handle plus post links when available. Use the host's inline post citation render when you have post citation IDs from X tools. Never invent URLs. Never append a trailing dump of unrelated Sources.

Read references/query-patterns.md when building search queries. Read references/failure-modes.md when the sample looks thin, mixed, or noisy.

Pipeline

Step 0 - Parse topic

  • Require a named topic (person, org, product, launch, event, controversy).
  • Strip intent modifiers for search entities (sentiment, drama, takes) but keep them as synthesis focus if the user asked for them.
  • Classify loosely: event | person/org | product/release | debate.

Step 1 - Optional entity web lookup (0 or 1 call)

If the topic is ambiguous or you lack an obvious official handle/name:

  • Make at most one web lookup to resolve identity.
  • Extract: canonical name, official @handle if stated, aliases, event date if the page states one.

If the topic is already clear (e.g. Kimi K3, @sama), skip web.

Step 2 - X entity grounding

  • Use x_user_search for likely official or primary accounts when useful.
  • Build aliases: exact phrase, alternate spellings, product codes, cashtags.
  • Prefer first-party from:handle when you have a confident handle.

Step 3 - Pulse (always first)

Run a cheap Latest keyword search with a short since: window to measure velocity. Example windows to try first:

  • Breaking candidate: last few hours (since:YYYY-MM-DD for today, Latest)
  • If almost empty: widen once (yesterday / last 2 days) before committing mode

Commit a mode and window:

Pulse signalModeDefault window
High volume, rising engagement, clear originBreakinglast 1–6 hours (minutes if still exploding)
Clear same-day event / launch chatterSame-daylast 24–48 hours
Ongoing debate, moderate velocityStorylast 3–7 days
Sparse posts, mostly references to older newsBackgroundlast 14–30 days; still prefer recent posts

State the chosen Window and Mode in the brief. Expand later only if:

  • No agreement on what happened
  • Missing first-party post from the obvious account
  • Debates point at an origin post you have not seen

When ranking, prefer recency over raw likes unless an older post is clearly the origin everyone quotes or replies to - then fetch that thread.

Step 4 - Search lattice (parallel)

Use multiple lanes. Cap total X tool calls roughly 8–14 for a normal run.

LaneToolGoal
Topx_keyword_search mode=TopHigh-engagement consensus
Latestx_keyword_search mode=Latest + time operatorsFresh narrative
Semanticx_semantic_searchParaphrases and adjacent framing
First-partykeyword from:handle when knownOfficial statement
Debatecontroversy / quote / counter-claim queriesDisagreement surface

Use advanced operators from references/query-patterns.md. Always keep the primary entity in the query. Drop off-entity viral noise.

Step 5 - Thread enrichment

x_thread_fetch the 3–8 highest-signal posts, prioritizing:

  1. Origin / announcement
  2. Official first-party
  3. Highest-engagement summary take
  4. Strongest steelman and strongest criticism
  5. Posts that define a camp split

Step 6 - Rank and cluster (in head, lightweight)

Rough score:

text
score = engagement × freshness_weight × authority_weight × on_entity
  • On-entity: must clearly be about the primary topic (or hard alias).
  • Authority (soft): official accounts, domain experts, primary reporters - never a hard allowlist; do not over-weight bluechecks alone.
  • Clusters: merge posts that make the same claim into one camp bullet.

Discard engagement bait that fails entity grounding.

Step 7 - Synthesize

Emit the brief using the template below. Do not dump raw ranked lists. Include at least 2–3 short attributed quotes from real posts when the sample has usable text.

If the sample is thin, say so. Prefer honest uncertainty over fake consensus.

Output template

Use this structure. Keep headings. No extra blog-style sections.

markdown
# /whathappened: {topic}

**Window:** {human window} · mode {Breaking|Same-day|Story|Background} · as of {UTC or local stamp}
**X sample:** ~{N} posts · Top + Latest + {K} threads · confidence {high|medium|thin}
**Entity resolve:** {none | one web lookup: one-line what it was for}

## What happened
2–5 sentences. Prefer first-party and origin posts. Stick to what X supports.

## Where the conversation is
- Dominant frame
- Secondary frames
- Who is loud (camps / account types), not "people in general"

## Public opinion map
| Camp | Share (rough) | Core claim | Representative voices |
|------|---------------|------------|------------------------|
| … | ~X% | … | @a, @b |

Label shares as qualitative judgment from this sample, not polling.

## The live debates
1. **{title}** - Side A vs Side B; stakes in one line; best evidence posts
2. …

## Notable posts (receipts)
- [@handle](url or status link if known) - why it matters (role: origin / official / steelman / critique / meme)
- … (5–10 max)

## Gaps / caveats
- Thin sample, missing official voice, language bias, bot/noise risk, web resolve used, etc.
- What would change this read if true

Formatting notes

  • Use plain hyphens -, not em dashes.
  • Neutral wording: "many posts claim", "a common critique is", not "everyone knows".
  • Rough camp percentages must be marked as rough sample judgment.
  • If confidence is thin, shrink the opinion map and expand Gaps.
  • End after Gaps. No trailing invitation spam unless the user asked follow-ups.

Pre-flight checklist (before first tool call)

  • Topic present (else ask)
  • X tools available (else refuse)
  • Web budget remaining: 0 or 1 resolve-only
  • No discovery request

Post-synthesis checklist (before send)

  • Window + mode stated
  • Every quoted line attributable to a fetched post
  • No web-derived "sentiment"
  • Camps grounded in multiple posts when confidence is high
  • Receipts are real and on-entity
  • Gaps honest about sample limits

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Whathappened AI skill do?

Brief what just happened on a topic and map public opinion from X (Twitter) only. Adaptive recency window biased to the freshest coherent story. Soft exception: at most one web lookup for entity resolution. Use when the user runs /whathappened, or asks what happened / what's going on / X or Twitter reaction / public opinion on X about a person, product, launch, or event. Grok Build only (requires native X tools). Neutral analyst tone. No discovery mode in v1.

Why use Whathappened on TypingMind?

Because you install it once and use it with any model. Whathappened is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Whathappened in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kunchenguid/whathappened/tree/main/skills/whathappened. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Whathappened?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Whathappened?

As many as you like. As long as a model supports skills, you can use Whathappened with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Whathappened AI skill free?

Yes. It is published on GitHub by kunchenguid under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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