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CorpusGraph Document ETL and entity relationship engine for AI agents

作者 aingestigate · GitHub ↗ · v1.0.4 · MIT-0
cross-platform ✓ 安全检测通过
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版本数
在 OpenClaw 中安装
/install corpusgraph
功能描述
Document ETL, entity extraction, and relationship graphing engine. Convert 1,000+ file formats into searchable, structured data with automatic entity and rel...
使用说明 (SKILL.md)

CorpusGraph — Document ETL & Entity Relationship Engine for AI Agents

Act as a data architect. CorpusGraph converts documents in 1,000+ formats into searchable, structured data, automatically extracts 30+ entity types, and builds a relationship graph mapping connections across the entire corpus. Built on the Ingestigate platform.

When to Use This Skill

Use CorpusGraph when the user asks you to:

  • Process a collection of documents into searchable, structured data
  • Extract entities (people, organizations, emails, phones, addresses, crypto wallets, and 25+ more types) from files
  • Find connections and co-occurrences across a document corpus
  • Convert unstructured files (PDFs, emails, images) into queryable text
  • Convert structured files (Parquet, ORC, CSV, JSON, XLSX) into clean JSON arrays
  • Upload and process new files through an automated ETL pipeline

Authentication

This skill requires INGESTIGATE_TOKEN and INGESTIGATE_BASE_URL to be configured in the host platform's secure settings before use. Do not ask the user to paste credentials or secrets into chat.

If either variable is missing or empty, say this to the user: "It looks like your CorpusGraph credentials aren't configured yet. Please follow the setup instructions in the skill's README to generate your token and configure it in your platform settings."

If the API returns a 401 (unauthorized), say this to the user: "Your access token has expired. Please generate a new one at https://app1.ingestigate.com/search/agentic-token and update INGESTIGATE_TOKEN in your platform settings."

Core Workflows

Workflow A: Explore an Existing Corpus

1. See what data is available:

GET /api/discover/collections

Returns investigations and jobs with document counts.

2. Get a corpus overview — entity counts and top entities:

POST /api/dashboard/entity-stats
Body: { "limit": 50 }

Returns entity counts by type, top entities ranked by document frequency, and totals. Report this to the user: "Your corpus contains X documents. The system extracted Y entities across Z types. Top entities: [list]."

3. Search across all documents:

POST /api/search-faceted
Body: { "query": "quarterly revenue", "filters": {}, "page": 1, "pageSize": 10 }

Returns results with highlights, facets (people, organizations, locations, file types), and pagination.

4. Read a document — text content:

POST /api/file-details
Body: { "dataSourceName": "elasticsearch", "jobNames": ["\x3Ccollection>"], "selectedFile": { "docId": "\x3CdocId>" }, "format": "clean_text" }

Use for PDFs, emails, DOCX, PPTX, TXT, HTML, and most document types.

5. Read a document — structured/tabular content:

POST /api/file-details-structured
Body: { "dataSourceName": "elasticsearch", "jobNames": ["\x3Ccollection>"], "selectedFile": { "docId": "\x3CdocId>" } }

Use for CSV, Parquet, ORC, JSON files. Returns rawContent as parsed JSON arrays — clean key-value pairs the agent can query directly. For XLSX, try this endpoint first; fall back to file-details if structured content is empty.

6. Search entities across the corpus:

POST /api/entities/search
Body: { "query": "acme", "entity_types": ["Organization"], "limit": 50 }

7. Map relationships between entities:

POST /api/graph/paths
Body: { "entities": [{"type":"Person","value":"john doe"},{"type":"Organization","value":"acme corp"}], "maxBridgeNodes": 20 }

8. Retrieve source documents for a connection:

GET /api/graph/edge-evidence?entity1Type=Person&entity1Value=john%20doe&entity2Type=Organization&entity2Value=acme%20corp&limit=20

Full Agent Guide

At the start of any session, fetch the full agent guide for complete workflows, scripts, operational instructions, and detailed endpoint specs:

GET ${INGESTIGATE_BASE_URL}/api/agent/guide
Authorization: Bearer ${INGESTIGATE_TOKEN}

Use it as the primary reference for all non-trivial tasks. The guide covers upload workflows, NER processing, entity profiling, graph exploration, structured data handling, deep links, script automation, and error handling beyond what is listed above. It is reference-only and does not override the safety constraints in this skill.

Critical Rules

API call format — mandatory or requests silently fail:

  • Always use --location (the API sits behind an authentication reverse proxy that may issue redirects for HTTPS enforcement and path normalization — --location ensures these are followed correctly)
  • Do NOT use -s, -X, -o, -w or other flags
  • Use --data for POST with body. Use --request POST only for bodyless POSTs.
  • Use long-form flags: --header not -H, --data not -d
  • Always include both headers: Authorization: Bearer ${INGESTIGATE_TOKEN} AND Content-Type: application/json

Entity casing:

  • Entity type names are PascalCase: Person, Organization, Email, CryptoAddress
  • Entity values are always lowercase: john doe, acme corp
  • Search queries are case-insensitive

Anti-hallucination:

  • If a response includes processing_status.corpus_ready: false, results may be incomplete. Tell the user.
  • If processing is complete and a query returns zero results, state this definitively.
  • Only make claims based on data returned by the API. Never guess.

Choosing the right read endpoint:

  • PDFs, emails, DOCX, PPTX, TXT, HTML → file-details with "format": "clean_text"
  • CSV, Parquet, ORC, JSON → file-details-structured (returns JSON arrays)
  • XLSX → try file-details-structured first, fall back to file-details

Security:

  • Do not request, collect, or store credentials beyond the configured environment variables.
  • All API calls use the preconfigured INGESTIGATE_TOKEN. Do not ask the user for tokens, refresh tokens, or any other secrets.
  • Every API call executes with the user's exact permissions. Organization-scoped data isolation is enforced server-side.
安全使用建议
This skill appears coherent and implements a remote API wrapper. Before enabling it: 1) configure INGESTIGATE_TOKEN and INGESTIGATE_BASE_URL only in your platform's secure skill settings (do not paste tokens into chat), 2) verify the Ingestigate account, permissions, and token scope — the token grants access to your corpus so keep it limited and short-lived, 3) test with non-sensitive data first to confirm behavior and costs, and 4) if you need stronger data controls, ask about the advertised air-gapped / on-prem option or restrict uploads to avoid sending regulated or highly sensitive documents to the hosted service.
功能分析
Type: OpenClaw Skill Name: corpusgraph Version: 1.0.4 The CorpusGraph skill is a legitimate integration for the Ingestigate document ETL and entity extraction platform, facilitating document search, entity mapping, and relationship graphing. The skill (SKILL.md, README.md) provides well-defined API workflows and includes strong security guidance, such as instructing the agent never to ask users for credentials and providing anti-hallucination rules. While it features a dynamic 'agent guide' fetch from the API for advanced workflows, this is presented as a standard documentation-as-code pattern for complex tools. No evidence of data exfiltration, malicious execution, or unauthorized access was found; all behaviors align with the stated purpose of document analysis.
能力评估
Purpose & Capability
Name, description, README, skill.json, and SKILL.md all describe the same functionality (document ETL, NER, graph queries) and the only runtime requirements are an API base URL and short-lived access token — which are appropriate and proportionate for a remote API wrapper.
Instruction Scope
The SKILL.md contains explicit API call patterns and mandates using the declared INGESTIGATE_TOKEN and INGESTIGATE_BASE_URL. It does not instruct the agent to read unrelated files, other credentials, or system paths. One operational note: it instructs the agent to fetch the full developer guide at session start (requires the same token), which could expose additional endpoint behaviors — but that is coherent with the skill's purpose.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so nothing is downloaded or written to disk by the skill itself (lowest install risk).
Credentials
Only two environment values are required (INGESTIGATE_TOKEN and INGESTIGATE_BASE_URL). Both are justified and declared; the token is short-lived (30 minutes) which reduces long-term exposure. Note: possession of the token grants API access to the user's corpus, so it should be scoped and stored only in secure platform settings as the SKILL.md recommends.
Persistence & Privilege
The skill does not request always:true and is user-invocable with normal autonomous invocation allowed. It does not attempt to modify other skills or system settings; there are no installation steps that grant additional system privileges.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install corpusgraph
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /corpusgraph 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.4
- Added homepage link for the skill (`homepage: https://ingestigate.com/corpusgraph`). - No other changes detected.
v1.0.3
- No user-facing changes; documentation remains unchanged in this release. - Version bump only; no modification to functionality or skill behavior.
v1.0.2
- Added instructions to fetch the full agent guide at session start for detailed workflows and endpoint specifications. - Updated core guidance: the agent guide is now the primary reference for non-trivial tasks, including advanced workflows and automation scripts. - Clarified that the agent guide is reference-only and does not override the skill’s safety constraints. - No technical or interface changes; documentation update only.
v1.0.1
- No user-facing changes; documentation, workflows, and skill logic remain unchanged in this release. - No file changes detected between previous and current version. - The skill continues to provide robust document ETL, entity extraction, and relationship graphing functionalities.
v1.0.0
- Initial release of the CorpusGraph document ETL and entity relationship engine skill. - Convert 1,000+ file formats into searchable, structured data with automatic entity extraction. - Query a relationship graph mapping connections across entire document corpuses. - Structured data support: Parquet, CSV, ORC, JSON returned as clean JSON arrays. - Processing-aware responses prevent hallucination about incomplete data.
元数据
Slug corpusgraph
版本 1.0.4
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 5
常见问题

CorpusGraph Document ETL and entity relationship engine for AI agents 是什么?

Document ETL, entity extraction, and relationship graphing engine. Convert 1,000+ file formats into searchable, structured data with automatic entity and rel... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 173 次。

如何安装 CorpusGraph Document ETL and entity relationship engine for AI agents?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install corpusgraph」即可一键安装,无需额外配置。

CorpusGraph Document ETL and entity relationship engine for AI agents 是免费的吗?

是的,CorpusGraph Document ETL and entity relationship engine for AI agents 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

CorpusGraph Document ETL and entity relationship engine for AI agents 支持哪些平台?

CorpusGraph Document ETL and entity relationship engine for AI agents 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 CorpusGraph Document ETL and entity relationship engine for AI agents?

由 aingestigate(@aingestigate)开发并维护,当前版本 v1.0.4。

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