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Data Context Extractor

Official
anthropics·vlatest·writing·Apache-2.0

Quickly identifies key entities, relationships, and relevant context from unstructured data sources for informed decision-making.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add anthropics/knowledge-work-plugins --skill data-context-extractor -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

anthropics

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned anthropics/knowledge-work-plugins at da38ec1ee8.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
da38ec1ee8
Manifest
data/skills/data-context-extractor/SKILL.md
Scanned
6 files, 932 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to automatically identify and extract relevant contextual information from unstructured data sources. It transforms raw, messy inputs into structured context that the agent can immediately use for reasoning and decision-making.

When to use it

  • Processing user uploads: Automatically parse PDFs, spreadsheets, or text files attached to a conversation to understand the background before answering questions.
  • Analyzing logs or reports: Extract key metrics, error codes, or specific event timelines from large technical documents without manual summarization.
  • Onboarding new data: Quickly ingest and structure incoming datasets (like customer feedback or market research) so the agent can query them effectively.
  • Context switching: Provide the agent with a summary of previous conversation threads or project documentation to maintain continuity in long-term tasks.

Key capabilities

  • Identification of relevant semantic entities within unstructured text.
  • Extraction and structuring of specific data points for immediate consumption.
  • Reduction of noise by filtering out irrelevant information from raw inputs.
  • Preparation of context specifically tailored for downstream reasoning tasks.

Example prompts

  • "Extract the key financial metrics and risk factors from this attached quarterly report."
  • "Analyze the provided customer support logs and list all unique error codes mentioned in the last 48 hours."
  • "Read this project documentation and pull out the specific dependencies required to run the local environment."

Tips & gotchas

Ensure your input data is reasonably well-formatted; while the skill handles unstructured text, highly corrupted files may yield incomplete results. For best accuracy, provide a clear instruction on what specific type of context you need extracted if the source material contains mixed topics.