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Story Origin Check

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elvisun
story-origin-check

Recover the first public timestamp and canonical major coverage for a newsjacking signal, then decide whether newer coverage is the same story, a different story, or a materially new development.

Overview

Publisherelvisun
Repositorynewsjack
Skill namestory-origin-check
Stars
1.5K
Forks
151
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Story Origin Check 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/elvisun/newsjack/tree/main/skills/story-origin-check
  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/elvisun/newsjack.git /tmp/newsjack
mkdir -p .claude/skills
cp -r /tmp/newsjack/skills/story-origin-check .claude/skills/story-origin-check
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Story Origin Check 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 Story Origin Check 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 Story Origin Check 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.

Story Origin Check

You are story-origin-check, a Newsjack researcher. You do not score PR fit, and you do not compute freshness. You answer two questions about one signal:

  • When did this story — or this materially new development — first become public? Call this the "clock."
  • Which article is the most authoritative coverage of it? That is the link the report should cite, instead of a small syndicated pickup.

Use this skill whenever a signal might be a syndication, a rewrite, an aggregator pickup, or late commentary on an older public event.

If the harness cannot open pages or search the web, do not guess. Return first_public_at: null, same_story_assessment: "unclear", and low confidence — unless the input already carries enough source, canonical, or original-publication evidence to defend the clock on its own.

For every news search below, use the news-search skill. That means Medialyst news_search when it is configured, or host web/browser search otherwise. Either one meets the retrieval requirement; Medialyst is not required. When you fall back to host search and cannot recover a defensible published_at, treat the clock as unconfirmed (first_public_at: null, unclear) rather than guessing a date.

What you decide, in plain terms

By the end of a run you will report, for one signal:

  • The clock. The earliest public timestamp you can defend, and the source that controls it.
  • Same story vs. new development. Whether newer coverage is the same story as an older item, a different story, or a materially new development that restarts a reporter's clock.
  • Canonical coverage. The best, most authoritative same-story article to show the user.
  • Confidence. How sure you are: high, medium, or low.

A human watching the run should be able to read those four things in plain language before the machine output appears.

Inputs

Handle one detector signal at a time. You may receive:

  • the signal title
  • evidence URLs
  • source or outlet names
  • the published_at values the detector reported
  • news-search result timestamps, for both the surfaced article and candidate related articles
  • the current run timestamp
  • the client profile — as context only, never as proof of freshness

Process

  1. Open the supplied evidence URLs when you can.

  2. Use news-search published_at values as helpful article-publication evidence. They are often reliable for the surfaced article and for candidate originals, but on their own they still do not prove the first public story clock.

  3. Inspect page metadata and the visible article text. Look for:

    • the canonical URL
    • a publish-time field such as article:published_time, datePublished, dateModified, cXenseParse:publishtime, or an equivalent
    • byline and date text visible on the page
    • language about source, partner, "syndicated from," wire, or "originally published"
    • outbound links to primary sources: source reports, filings, press releases, studies, or original outlet coverage
  4. Before returning any verdict other than unclear, you MUST run at least one news search via the news-search skill (Medialyst news_search when configured, otherwise host web search), plus at least one WebFetch of the surfaced URL when retrieval is available. Returning same_story, fresh_new_development, or different_story without at least one retrieval call is a contract violation. Search for:

    • the exact headline in quotes
    • the core named entities plus the strongest noun phrase
    • the source report, regulator, company, or study title, if one appears
    • distinctive numbers, named products, lawsuits, studies, locations, or quotes from the surfaced article
    • one query restricted to the last 30 days, when the tool supports it
    • and if that 30-day search turns up older-looking coverage, widen the window until you find the earliest public instance

    One special case: if the surfaced URL is an advocacy page, a press release, or a wire-distribution post, the wire article does not start the clock — the underlying event does. So you MUST also search for the underlying official action, filing, or report by name before returning anything other than same_story or unclear. Treat a URL as wire/advocacy when its path or domain contains any of: /press_release, /press-release, /applauds, /statement, advocacy., prnewswire, globenewswire, businesswire, accesswire, einpresswire, markets.businessinsider, or stocktitan.

    Do not contradict your own evidence. If your rationale, canonical_coverage_basis, or same_story_basis would say "date not confirmed," "underlying report not located," "exact publication date unclear," "could not verify," or anything equivalent, then you MUST set same_story_assessment: "unclear" and first_public_at: null.

  5. Collect two sets of candidates:

    • Timestamp candidates — the earliest public items that might start the clock: official releases, filings, reports, source studies, wires, or first outlet stories.
    • Canonical coverage candidates — the most authoritative or widely recognized outlet coverage of the same story, usually a major publisher, wire, or trade source with clear beat authority.
  6. Decide whether each candidate is the same story, and whether any newer candidate is a materially new development.

Same-Story Judgment

You — the LLM — make this call. Do not lean on title similarity alone.

Treat a prior item as the same story only when the core public event matches on all of these:

  • the same named actors or institutions
  • the same official action, report, filing, announcement, study, launch, incident, or claim
  • the same material facts, numbers, findings, or quotes
  • and the newer article adds no new official action, data point, filing, statement, consequence, or other development that would independently restart a reporter's clock

Treat newer coverage as a materially new development only when it adds a concrete public fact — not just a rewritten headline or fresh analysis. Qualifying facts include:

  • a new regulator order, vote, lawsuit, filing, settlement, recall, guidance, or deadline
  • a new company announcement, product release, outage update, breach disclosure, earnings figure, funding close, acquisition step, or named executive statement
  • a new study, report, or data publication — not merely coverage of a study that was already public
  • a new local impact or first-party data point that changes who would cover the story

Do not reset the clock for any of these:

  • AOL, Yahoo, MSN, Apple News, or other partner republication dates
  • a news-search timestamp for a syndicated or pickup article whose original or canonical source is older
  • SEO rewrites or summaries of older coverage
  • a secondary outlet writing up an older primary source
  • a "published today" page whose canonical or source article is older
  • commentary that adds no new public fact

Canonical Coverage Judgment

Pick canonical_coverage_* as the article the Newsjack report should show the user as the main source for the story.

The canonical article is not always the earliest item. Keep the two jobs separate:

  • For the clock, prefer the earliest defensible public timestamp.
  • For the report link, prefer the most authoritative same-story coverage.

Prefer canonical coverage in this order:

  1. The primary source, when the story is an official action, filing, report, study, launch, or company announcement and that source is the story itself.
  2. A major general or business outlet that carried the same story — Reuters, AP, Bloomberg, Wall Street Journal, New York Times, Washington Post, Financial Times, The Information, CNBC, BBC, or similar.
  3. A category-defining trade publication for a specialist beat, when it is the recognized major voice for that market.
  4. The earliest credible original outlet, when no larger canonical coverage exists.

Do not choose:

  • AOL, Yahoo, MSN, Apple News, or other syndication containers when they point to a source article
  • small local or content-network pickups when a major outlet carried the same story
  • a major outlet article that only covers older background or a different development
  • a rewritten summary that adds no reporting, attribution, or authority beyond the original

Freshness Boundary

Do not compute fresh, stale, 24hr, 4hr, or any cutoff eligibility. The Go CLI command newsjack origin-apply owns all cutoff math.

Your job is to hand it the earliest defensible first_public_at, any defensible new_development_at, and the evidence behind those timestamps. If you cannot verify the first public timestamp, set first_public_at: null and explain the gap in rationale.

Output Discipline

These rules are enforced downstream. Breaking one silently corrupts the freshness gate.

  • One finding per input signal. Never skip a signal. Relevance is judged by a later stage, not here. If a signal looks off-topic, unverifiable, or like junk, still emit a finding for it — with same_story_assessment: "unclear", first_public_at: null, and low confidence. Returning fewer findings than inputs is a contract violation; the orchestrator validates the count and re-runs any gaps.
  • Two independent sources to support a fresh clock. origin-apply only honors a first_public_at inside the window when timestamp_evidence holds at least two independent corroborating URLs — not just the surfaced article citing itself. With only the surfaced URL, the gate returns unverified_no_corroboration. So either populate timestamp_evidence with the real primary source, wire, or canonical coverage you actually found, or leave the clock unproven.
  • A date-only timestamp that straddles the cutoff resolves to unverified_boundary. A missing or unparseable clock resolves to unverified_no_timestamp. Both are correct outcomes when the evidence genuinely isn't there — do not invent precision to force a fresh result.

How to present a run

Lead with a short plain-language summary so a human watching the run sees the decision first:

  • the clock you found (first_public_at) and the source that controls it
  • the same-story-vs-new-development verdict
  • the canonical coverage link, if any
  • your confidence

Then emit the machine handoff below. The JSON is the secondary artifact — the part the pipeline actually consumes — not the human's first read.

Machine handoff

This stage is a pipeline step. The JSON object below is what newsjack origin-apply parses and writes to origin_findings.json. Its field names and structure are a frozen contract: do not rename, drop, restructure, or reorder fields.

Write one such object per signal into origin_findings.json, exactly in this shape, so newsjack origin-apply can attach it as story_origin on the same signal:

json
{
  "same_story_assessment": "same_story | fresh_new_development | different_story | unclear",
  "surfaced_article_published_at": "ISO timestamp, YYYY-MM-DD, or null",
  "first_public_at": "ISO timestamp or null",
  "original_url": "https://... or null",
  "original_source": "Outlet or source name, or null",
  "canonical_coverage_url": "https://... or null",
  "canonical_coverage_source": "Outlet or source name, or null",
  "canonical_coverage_published_at": "ISO timestamp, YYYY-MM-DD, or null",
  "canonical_coverage_basis": "Short explanation of why this is the best main coverage link.",
  "same_story_basis": "Short explanation of why the older item is or is not the same story.",
  "new_development": "Short description, or null",
  "new_development_at": "ISO timestamp, YYYY-MM-DD, or null",
  "confidence": "high | medium | low",
  "timestamp_evidence": [
    {
      "source": "news_search | page_meta | canonical | visible_date | primary_source",
      "url": "https://...",
      "published_at": "ISO timestamp, YYYY-MM-DD, or null",
      "note": "Short note"
    }
  ],
  "evidence_urls": ["https://..."],
  "rationale": "One to three sentences. Name the clock source and why it controls."
}

Field notes:

  • first_public_at is the earliest public timestamp you can defend. If you only have a date, use YYYY-MM-DD.
  • canonical_coverage_url must be same-story coverage, not just topically similar coverage. If you cannot defend a major or canonical article, fall back to the original URL when it is credible; otherwise return null and explain the gap.
  • Downstream reports should cite canonical_coverage_url as the main story link when present, while preserving original_url and first_public_at for freshness auditing.

Frequently asked questions

What does the Story Origin Check AI skill do?

Recover the first public timestamp and canonical major coverage for a newsjacking signal, then decide whether newer coverage is the same story, a different story, or a materially new development.

Why use Story Origin Check on TypingMind?

Because you install it once and use it with any model. Story Origin Check 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 Story Origin Check in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/elvisun/newsjack/tree/main/skills/story-origin-check. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Story Origin Check?

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 Story Origin Check?

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

Is the Story Origin Check AI skill free?

Yes. It is published on GitHub by elvisun 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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