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data-ingestion-unstructured

data-ingestion-unstructured is a skill for Claude Code, Codex from ibm-self-serve-assets/building-blocks. It costs 77 tokens per session (1,094 once invoked), scanned A, original, Apache-2.0.

Guidance for building pipelines that extract useful text and metadata from PDFs, Word documents, web pages, and images. It describes sending the processed content from IBM Cloud Object Storage into IBM watsonx.data for search and retrieval.

In plain words
What is it for?
Use it to plan document ingestion with Docling or Unstructured, handle OCR, choose chunk sizes for retrieval-augmented generation, extract source details, and configure IBM DataStage and cloud storage connections.
Why use it?
It helps turn messy documents into consistently processed, searchable data. It also addresses document parsing, text splitting, metadata, embeddings, and IBM Cloud authentication.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 28repo yesterday A scan SkillSpector: warn 77 tokens original Apache-2.0

Good fit Use it to plan document ingestion with Docling or Unstructured, handle OCR, choose chunk sizes for retrieval-augmented generation, extract source details, and configure IBM DataStage and cloud storage connections.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ibm-self-serve-assets/building-blocks/data-ingestion-unstructured
View source ↗ ibm-self-serve-assets/building-blocks ibm-self-serve-assets.github.io
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ibm-self-serve-assets/building-blocks --skill data-ingestion-unstructured
Clone the repo
git clone --depth 1 https://github.com/ibm-self-serve-assets/building-blocks

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for data-ingestion-unstructured

README.md
[![agentmods](https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/data-ingestion-unstructured/github.svg)](https://agentmods.dev/skills/ibm-self-serve-assets/building-blocks/data-ingestion-unstructured)
Your own site
<a href="https://agentmods.dev/skills/ibm-self-serve-assets/building-blocks/data-ingestion-unstructured"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/data-ingestion-unstructured/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for data-ingestion-unstructured

Your own site · 80×15
<a href="https://agentmods.dev/skills/ibm-self-serve-assets/building-blocks/data-ingestion-unstructured"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/data-ingestion-unstructured.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,094 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium Data Exfiltration · line 128
    Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.
    Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00077 $0.01094
Opus 5.5 $0.00031 $0.00438
Sonnet 5.5 $0.00015 $0.00219
Haiku 4.5 $0.00008 $0.00109

Measured 2mo ago against content hash 1c57ae719635, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

data-ingestion-unstructured scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

ibm-bob/skills/data-ingestion-unstructured/SKILL.md · 130 lines

How it starts

The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.

IBM Unstructured Data Ingestion Builder

Purpose

Expert guidance for building unstructured data ingestion pipelines using IBM UDI (Unstructured Data Ingestion) and IBM Docling — processing documents (PDF, DOCX, HTML, images) from IBM COS into IBM watsonx.data vector storage.

IBM Cloud Product Coverage

IBM Cloud Product Usage
IBM UDI (Unstructured Data Integration) DataStage-based unstructured document processing
IBM watsonx.data Target: Iceberg tables for metadata; Milvus/OpenSearch for vectors
IBM Cloud Object Storage Source document storage
IBM watsonx.ai Embedding generation for vectorised chunks
IBM Cloud IAM POST /identity/token (apikey grant)

Rules

  • Use docling for high-quality PDF/DOCX parsing (IBM's document AI library)
  • Use unstructured as fallback for broad format support (HTML, PPTX, email)
  • IBM UDI via DataStage: use IBM.UDI connector in DataStage job definition
  • Chunking: RecursiveCharacterTextSplitter(chunk_size=512, chunk_overlap=128) for RAG
  • Always extract title, source path, page number, and chunk_seq as metadata
  • COS download: always use ibm-cos-sdk with IAM OAuth (not HMAC) in Python

Scope

  • IBM UDI DataStage connector configuration
  • IBM Docling document parsing (PDF, DOCX, images)
  • unstructured.io multi-format parsing (HTML, PPTX, email, Excel)
  • OCR for scanned PDFs and image-based documents
  • Chunking strategies: fixed-size, semantic, sentence-based
  • Metadata extraction and enrichment
  • IBM COS to watsonx.data pipeline patterns

Procedure

Phase 1: IBM Docling PDF Parsing

from docling.document_converter import DocumentConverter

converter = DocumentConverter()
result = converter.convert(cos_local_path)
doc = result.document

# Extract text preserving document structure
markdown_text = doc.export_to_markdown()
# or JSON structure
json_doc = doc.export_to_dict()

Phase 2: IBM COS Document Download

import ibm_boto3
from ibm_botocore.client import Config

cos = ibm_boto3.client("s3",
    ibm_api_key_id=COS_API_KEY,
    ibm_service_instance_id=COS_INSTANCE_CRN,
    config=Config(signature_version="oauth"),
    endpoint_url=COS_ENDPOINT,
)
cos.download_file(bucket, key, local_path)

Read the full file on GitHub · 130 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 130 lines · 77 tokens per session scan A 1c57ae719635

Subscribe to this mod's changes

data-ingestion-unstructured is a skill published in the GitHub repository ibm-self-serve-assets/building-blocks (28 stars, last pushed yesterday), licensed Apache-2.0. It adds 77 tokens to every session and 1,094 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Data and AIDocumentsPDF
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