hyper-extract
/hyper-extract
Operate yifanfeng97/Hyper-Extract, the Python `he` CLI for extracting structured knowledge from documents with templates, provider configuration, indexing, search and an MCP server. Use when users name Hyper-Extract, `he`, or ask about this document-to-knowledge CLI. It is a configurable extraction workflow, not a general-purpose ontology editor or database; route graph pipeline questions to Semantica and visual OWL/SKOS editing to OrionBelt.
- Author
- akillness ↗
- Repository
- jeo-skills ↗
- Licence
- MIT
- Last repository change
- 13.11.2026
Assessment and security
- Files in this package
- 5
- Scripts
- 1
- HTML comments
- 0
- URLs in SKILL.md
- 1
No signals detected. Repository changed on 13.11.2026, without references to retired models or APIs.
MIT, open: use and modify while retaining author attribution.
- 1 scripts in this package. Review them before installing, as Claude may execute them.
Scripts: scripts/preflight.py
What it does and when to use it
Operate yifanfeng97/Hyper-Extract, the Python `he` CLI for extracting structured knowledge from documents with templates, provider configuration, indexing, search and an MCP server. Use when users name Hyper-Extract, `he`, or ask about this document-to-knowledge CLI. It is a configurable extraction workflow, not a general-purpose ontology editor or database; route graph pipeline questions to Semantica and visual OWL/SKOS editing to OrionBelt.
Original author description
Operate yifanfeng97/Hyper-Extract, the Python `he` CLI for extracting structured knowledge from documents with templates, provider configuration, indexing, search and an MCP server. Use when users name Hyper-Extract, `he`, or ask about this document-to-knowledge CLI. It is a configurable extraction workflow, not a general-purpose ontology editor or database; route graph pipeline questions to Semantica and visual OWL/SKOS editing to OrionBelt.
How it works
- Instructions
- Examples
- Best practices
- References
SKILL.md preview
--- name: "hyper-extract" description: "Operate yifanfeng97/Hyper-Extract, the Python `he` CLI for extracting structured knowledge from documents with templates, provider configuration, indexing, search and an MCP server. Use when users name Hyper-Extract, `he`, or ask about this document-to-knowledge CLI. It is a configurable extraction workflow, not a general-purpose ontology editor or database; route graph pipeline questions to Semantica and visual OWL/SKOS editing to OrionBelt." allowed-tools: Bash Read Grep Glob compatibility: "Requires Python 3.11+ and the package's selected provider/configuration; remote providers may incur cost and receive document content." metadata: version: "1.0.0" source: "https://github.com/yifanfeng97/Hyper-Extract" upstream_commit: "190dbf561df2c6e72af3f05b59b6abaf54b8a130" --- # Hyper-Extract ## Instructions 1. Classify the task as document parsing/extraction, index/search, configuration, template management, or MCP. Check the pin and installed CLI help before using exact flags. 2. `he parse <input> -t <template> -o <output>` is a documented command shape; preview the source files and output directory first. Extraction may send document data to a configured model provider. Obtain explicit approval for uploads, provider calls, cost, and output writes. 3. Inspect provider/config location and permissions before recommending changes. The pinned implementation stores config under `~/.he/config.toml` and restricts access where supported. Never print or request API key values; use provider environment settings or secure local entry only after approval. 4. Do not infer MCP safety from CLI use. Review transport, tool scope, credentials and client config; obtain approval before server start or registration. ## Examples - “Extract this local Markdown file using a template, but do not call a provider yet.” - “Explain the difference between `he parse` and `he search`.” - “Troubleshoot an `he config` issue without exposing API keys.” ## Best practices - Start with `he --help`, `he config --help`, and `he list template`; use a small non-sensitive fixture before production documents. - Keep raw inputs, generated knowledge artifacts, and indexes in distinct destinations with explicit retention and access rules. - Read [`references/upstream.md`](references/upstream.md) for current provider and MCP boundaries. The offline helper verifies only selected file hashes and PATH tool presence, never provider/runtime readiness. ## References - [`references/upstream.md`](references/upstream.md) - install/CLI, provider config, MCP scope, limits, license and approvals. - [`references/source.json`](references/source.json) - selected pinned file SHA256s; not a whole-revision attestation. - [`evals/evals.json`](evals/evals.json) - authored routing and boundary scenarios, not executed model-quality tests.
Files in this package (5)
- SKILL.md 3 KB
- evals/evals.json 2 KB
- references/source.json 2 KB
- references/upstream.md 3 KB
- scripts/preflight.py 10 KB
Versions
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Database snapshot: 13.11.2026 · package version c3ca5cd12cb7 (SHA-256 digest of the entire package)
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