# X Posts To Kg Ingestion

> Search X (formerly Twitter) posts and ingest content into the Knowledge Graph with automatic classification, tiered memory, and self-evolution awareness. Uses the xAI Responses API (grok-4.3) for search, the UniversalKnowledgeClassifier for scoring, and XIngestionBridge for structured KG persistence. Supports tweets, threads, and X Articles (long-form content). Triggers on "search X", "ingest X posts", "browse X", "x to kg", "x research", "social media ingestion".

- Skill: `knuckles-team/x-posts-to-kg-ingestion` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add knuckles-team/x-posts-to-kg-ingestion`
- Raw SKILL.md: https://api.skillmd.com/api/skills/knuckles-team/x-posts-to-kg-ingestion/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Research & Search
- Author: Knuckles-Team (https://skillmd.com/u/knuckles-team)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/knuckles-team/x-posts-to-kg-ingestion

---


# X Posts to KG Ingestion Workflow

Searches X posts for a given query and ingests the content, author metadata,
engagement statistics, and extracted concepts directly into the Knowledge Graph.
Uses the `UniversalKnowledgeClassifier` for importance scoring and
`XIngestionBridge` for structured persistence.

## Architecture

```mermaid
graph LR
    A["User Query / URL"] --> B["x_search / browse_x_post"]
    B --> C["XIngestionBridge"]
    C --> D["UniversalKnowledgeClassifier"]
    D --> E{Tier?}
    E -->|critical/high| F["SocialPostNode\n(permanent)"]
    E -->|standard| G["SocialPostNode\n(decays)"]
    E -->|ephemeral| H["SocialPostNode\n(fast decay)"]
    F --> I["EvolutionCandidateNode"]
    I --> J["→ knowledge-assimilation"]
```

## Execution Steps

### Step 0: x-search-agent
Search X using `x_search` for a topic query, or browse a specific post URL
using `browse_x_post` with `auto_ingest=True`.

**For topic search:**
```
Use x_search with query: "{{task}}"
```

**For specific post:**
```
Use browse_x_post with url: "{{task}}", auto_ingest: true
```

When `auto_ingest=True`, the browse tool automatically:
1. Retrieves the post via xAI Responses API (grok-4.3)
2. Classifies content via UniversalKnowledgeClassifier
3. Creates SocialPostNode + Person + KBConcept nodes
4. Creates EvolutionCandidateNode if evolution potential ≥ 0.6

Expected: posts with content, engagement metrics, classification results

### Step 1: graph-os
For search results (not auto-ingested), manually ingest each result into the KG
using the XIngestionBridge pattern.

For each result from Step 0:

1. Create SocialPost node:
```
Use mcp_graph-os_graph_write with action: "add_node",
node_type: "SocialPost",
node_id: "social:x:<post_id>",
properties: '{
  "post_id": "<id>",
  "author_handle": "<handle>",
  "content_text": "<text>",
  "post_url": "<url>",
  "post_type": "tweet|article|thread",
  "importance_score": <classifier_score>,
  "is_permanent": <true|false>,
  "evolution_potential": <score>
}'
```

2. Create Person node and link:
```
Use mcp_graph-os_graph_write with action: "add_node",
node_type: "Person", node_id: "person:x:<handle>"

Use mcp_graph-os_graph_write with action: "add_edge",
source_id: "social:x:<id>", target_id: "person:x:<handle>",
rel_type: "CREATED_BY_PERSON"
```

3. For each extracted concept, create KBConcept + ABOUT edge

4. For X Articles (long-form content), fetch full article:
```
Use read_url_content with url: "<article_url>"
```
Then ingest via:
```
Use mcp_graph-os_graph_ingest with action: "ingest", target_path: "<url>"
```
Link SocialPost → Article via PROMOTES_RESEARCH edge.

Expected: cypher, ingest, concepts linked
Depends On: Step 0

## X Article Detection

X Articles are long-form posts (up to ~100K chars) that the xAI API returns
as tweets but contain article links. The bridge detects these by:

1. Content length > 3000 characters
2. URL patterns matching `x.com/*/articles/*`

When detected, the article is fetched via browser/read_url_content and
ingested through the full KBIngestionEngine pipeline, producing:
- `Article` node with summary, content, word count
- `KBConcept` nodes for extracted concepts
- `KBFact` nodes for atomic facts
- `PROMOTES_RESEARCH` edge from the originating SocialPost

## Classification Tiers

| Tier | Importance | Permanent | Decay | Evolution |
|------|-----------|-----------|-------|-----------|
| Critical | ≥ 0.9 | ✅ | None | Auto-trigger |
| High Value | 0.7–0.9 | ✅ | None | Flagged |
| Standard | 0.4–0.7 | ❌ | 5%/day | No |
| Ephemeral | ≤ 0.3 | ❌ | 10%/day | No |

## References

- [knowledge-assimilation](../../research-workflows/knowledge-assimilation/SKILL.md) — Full evolution pipeline
- The package-specific X architecture guide is owned by `agent-utilities` at
  `docs/guides/x-assistant.md`; it is not bundled with this workflow.

## Execution

Run this workflow as a dependency-ordered DAG. Steps with no unmet `depends_on` run in parallel; dependents run after their prerequisites complete.

- **Run first (in parallel):** Step 0 — x-search-agent; Step 1 — graph-os

**Execution:** If graph-os is reachable, offload the whole DAG via `graph_orchestrate action=execute_workflow` (or the `kg-delegate` skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet `depends_on` in parallel, then their dependents.