Timeline Builder
AI Skills

Timeline Builder

Skip to main content
< All Topics
Print

Timeline Builder

Posted
Updated
ByPU Publish
0 out of 5 stars
5 Stars 0%
4 Stars 0%
3 Stars 0%
2 Stars 0%
1 Stars 0%

Build dated, source-cited timelines through conversational intake, web research, event extraction, and Cool Timelines Pro publishing.

Workflow


Phase 1  Intake ──► Phase 2  Research ──► Phase 3  Extract
  │                                           │
  └─ user refines scope ◄── Phase 4  Review ◄─┘
                                 │
                           Phase 5  Publish ──► Phase 6  Frontmatter

## Phase 1: Intake and Scoping

Accept the user’s request and resolve it into structured parameters:

| Parameter | Question to resolve | Default |

|———–|——————-|———|

| Subject | Who or what is this timeline about? | (required) |

| Scope | Date range, geographic focus, topical focus? | All available dates |

| Source strategy | Existing KB document, web research, or both? | See decision tree |

| Timeline type | accountability, legislative, legal, general? | Infer from category |

| Output target | Which KB document gets the timeline frontmatter? | Existing doc or new |

### Decision tree

– User names a KB slug → load that document as primary source, supplement with web research if dates are sparse.

– User names a topic without a KB doc → research-first mode via Tavily.

– User says both → merge KB body + fresh web research.

If the request is ambiguous, ask one clarifying question before proceeding.

### PU category → timeline type mapping

| KB category | Timeline type | Extraction focus |

|————-|————–|——————|

| 01-convicted-and-indicted | accountability | Indictments, convictions, sentences, appeals |

| 02-trump-family-and-associates | accountability | Business deals, appointments, investigations |

| 03-trump-administration | accountability | Official actions, firings, EOs, scandals |

| 04-federal-legislators | accountability | Votes, statements, committee actions |

| 05-state-legislators | accountability | State-level actions, elections, legal |

| 06-political-operatives | accountability | Campaign activities, investigations, connections |

| 07-media-fox-news-hosts | accountability | Statements, lawsuits, retractions |

| 09-media-other | accountability | Statements, platform actions, investigations |

| voting | legislative | Registration deadlines, law changes, court rulings |

| legal | legal | Court decisions, EOs, enforcement actions |

| All others | general | Key developments, policy changes, incidents |

Phase 2: Web Research

Compose with Tavily to gather date-bearing source material.

  1. Run tvly search queries targeting the subject + date-bearing keywords (e.g., “Stephen Miller immigration policy timeline 2017-2026”)
  2. For each promising result, run tvly extract to pull full article content
  3. For deep topics, run tvly research for a comprehensive synthesis
  4. Capture published_date from every result (per the Publication Date Rule in patriot-content-authoring)
  5. Store results in a structured intermediate format

For accountability subjects add searches for:

  • "{subject}" indictment OR conviction OR investigation OR resignation
  • "{subject}" executive order OR appointment OR fired OR sanctions

If published_date cannot be determined, record "[publication date not available]".

Phase 3: Event Extraction

Use Claude to extract structured timeline events from all gathered material.

Event schema


{
  "events": [
    {
      "date": "MM/DD/YYYY",
      "title": "Short event title (10 words max)",
      "description": "One-paragraph summary with source attribution",
      "source_url": "https://...",
      "source_name": "Publication name",
      "source_date": "Month Day, Year",
      "confidence": "high|medium|low"
    }
  ],
  "subject_name": "Full name or topic",
  "date_range": "YYYY – YYYY",
  "timeline_type": "accountability|legislative|legal|general"
}

Confidence tiers

Tier Definition Examples
high Primary source or official record Court filings, government press releases, executive orders
medium Credible secondary reporting AP, Reuters, NYT, WaPo, ProPublica
low Single-source reporting or inferred date Blog posts, social media, estimated dates

Extraction rules

  • Extract only events with specific, determinable dates
  • Use the first of the month if only month+year is known
  • Cite the source for every event
  • Order chronologically, earliest first
  • Minimum 3 events, maximum 30 events
  • Deduplicate events appearing in multiple sources (keep highest-confidence version)

Phase 4: User Review

Present extracted events for review before publishing:


Timeline: {subject_name} ({date_range})
Type: {timeline_type}
Events: {count}

 1. [MM/DD/YYYY] {title}
    {description}
    Source: {source_name}, {source_date}. {source_url}
    Confidence: {confidence}

The user may:

  • Approve → proceed to Phase 5
  • Edit an event (date, title, description)
  • Remove an event
  • Add an event manually
  • Request more research on a gap
  • Change scope (“extend to 2026”, “focus only on legal actions”)

Loop back to Phase 2 or 3 as needed until the user approves.

Phase 5: Publish to Cool Timelines Pro

Once approved, publish to WordPress using the existing timeline infrastructure.

Every event date must be in Cool Timelines Pro format: MM/DD/YYYY 12:00 am.

Using WPTimelineClient:

  1. ensure_story_category("PU: {title}", "pu-{slug}") — create/find category
  2. create_story() per event — with title, content, date_str, category_ids, story_order
  3. build_shortcode() — generate the [cool-timeline] shortcode

Phase 6: Store in Frontmatter

Update the target KB document’s YAML frontmatter:


timeline_shortcode: "[cool-timeline category=\"pu-{slug}\" ...]"
timeline_story_ids: [11422, 11424, 11425]
timeline_category: "pu-{slug}"

These fields are:

  • Protected during normal editor saves (doc_service.py)
  • Injected into WordPress post content at publish time (pu_publish.py)
  • Not part of the content hash (timeline changes alone do not trigger republish)

After writing frontmatter, run pu_publish.py --apply --only {slug} to push.

Composed skills

Skill Role
tavily-search Web search for date-bearing events
tavily-extract Full article content from promising URLs
tavily-research Deep synthesis for complex multi-year topics
patriot-content-authoring Publication date rule, frontmatter conventions
accountability-profile-verification Source citation standards for accountability timelines
fact-checking Verify extracted events when confidence is low
patriot-sanity-check Final proportionality and accuracy check

Guardrails

  • Apply patriot-private-citizen-inclusion-gate before building timelines for any individual.
  • Apply patriot-sanity-check on the final event list before publishing.
  • Never include events sourced solely from social media without corroboration.
  • Events tagged confidence: low must be flagged to the user during review.
Was this article helpful?
0 out of 5 stars
5 Stars 0%
4 Stars 0%
3 Stars 0%
2 Stars 0%
1 Stars 0%
5
Please Share Your Feedback
How Can We Improve This Article?
Table of Contents

Related Articles