Skills context7-integration
📦
context7-integration
Content revision r1 High Risk ⚡ Contains scripts⚙️ External commands🌐 Network access🔑 Env variables
Integrate Context7 Knowledge Retrieval
Document-heavy apps need relevant answers without exposing every file to every user. This skill shows Context7 ingestion, search, and role-scoped retrieval patterns.
Supports: Claude Codex Code(CC)
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Review the plan and obtain explicit user consent before changing files.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Agent request
Review the Skillstore skill "context7-integration" from https://skillstore.io/skills/awais68-context7-integration.md and its manifest at https://skillstore.io/api/skills/awais68-context7-integration/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "context7-integration". Search for fee refund policy details for a parent user.
Expected outcome:
Returns matching policy documents, a concise context summary, similarity scores, and source titles for review.
Using "context7-integration". Ingest a new attendance procedure for one school.
Expected outcome:
Creates metadata with title, module, category, allowed roles, tenant scope, and source tracking before upload.
Using "context7-integration". Prepare retrieved knowledge for an AI chat response.
Expected outcome:
Formats selected chunks with source labels and trims long context to fit the configured token budget.
Security Audit
High Riskv9 • 7/5/2026 Open versioned report
Most shell, script, obfuscation, and reconnaissance alerts are false positives from Markdown formatting, frontmatter, and access-control examples. The skill does contain legitimate network and environment-secret access for Context7 API calls. Additional review should address prompt-injection exposure in retrieved context and broad default document access.
2
Files scanned
1,052
Lines analyzed
15
Review items
0
False positives ignored
Confirmed security concerns (2)
High
Untrusted Retrieved Content Added to Prompts
The context shaper formats retrieved document text directly into AI prompt context and only normalizes or truncates it. Malicious document content could instruct the model to ignore system rules unless explicit untrusted-context boundaries are added.
The cited code builds prompt context from document content and the formatting helper only trims whitespace. No prompt-injection boundary, instruction filtering, or safety wrapper is shown.
Medium
Default Document Access Allows All Roles
Document metadata treats an empty role list as visible to all roles, and ingestion defaults missing roles to all. Sensitive documents can become broadly searchable if callers omit explicit access metadata.
The metadata comment states that an empty role list means all roles, and the API route uses all when request roles are missing. This is a clear least-privilege risk.
Capability review items (15)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
Low
HTTP client library
def _request(
This is the request helper for the Context7 client, with the actual session request nearby. It is legitimate, but it centralizes outbound network calls.
Low
HTTP client library
response = session.request(
The code calls session.request against self.base_url and endpoint. This is a direct outbound HTTP request path.
Low
HTTP client library
return self._request("POST", "/v1/documents", json=payload)
The code posts document content and metadata to /v1/documents. This is intended ingestion, but it is security-relevant data transfer.
Low
HTTP client library
response = self._request(
Batch ingestion sends multiple document payloads through the Context7 request helper. This is intended, but it can transfer substantial document content externally.
Low
HTTP client library
response = self._request("POST", "/v1/search", json=payload)
Search sends queries and filters to the Context7 API. This is normal for the feature, but user queries and tenant filters leave the application boundary.
Low
HTTP client library
response = self._request(
The client retrieves a document through the Context7 API. It is legitimate functionality with outbound network dependency.
Low
HTTP client library
self._request(
The client sends a DELETE request to the Context7 API. It is intended management behavior that can modify remote stored content.
Low
HTTP client library
response = self._request("GET", "/v1/documents", params=params)
The client lists remote documents through the Context7 API. It is intended behavior but exposes metadata through an outbound request.
Low
HTTP client library
response = self._request(
The client requests remote namespace statistics through the Context7 API. It is a legitimate outbound network operation.
Low
Python HTTP libraries
self._session = requests.Session()
The snippet creates a requests session used by the Context7 client. It is legitimate client code, but it enables outbound API traffic from the skill examples.
Low
Hardcoded URL
self.base_url = base_url or os.getenv("CONTEXT7_API_URL", "https://api.context7.com")
The client defaults to https://api.context7.com, so document and query data can leave the local application. This is intended behavior but is real external network egress.
Low
Python getenv function
self.api_key = api_key or os.getenv("CONTEXT7_API_KEY")
The client reads CONTEXT7_API_KEY from the environment. This is normal configuration, but it brings a secret into the runtime client.
Low
Python getenv function
self.base_url = base_url or os.getenv("CONTEXT7_API_URL", "https://api.context7.com")
The client reads CONTEXT7_API_URL from the environment. That value controls the destination for API traffic, so it is security-relevant configuration.
Low
getenv function call
self.api_key = api_key or os.getenv("CONTEXT7_API_KEY")
The getenv call reads CONTEXT7_API_KEY for API authentication. This is legitimate secret access and should be handled carefully.
Low
getenv function call
self.base_url = base_url or os.getenv("CONTEXT7_API_URL", "https://api.context7.com")
The getenv call reads CONTEXT7_API_URL and can change the remote endpoint. This is legitimate but security-relevant environment access.
Risk Factors
⚡ Contains scripts (1)
⚙️ External commands (29)
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🌐 Network access (12)
🔑 Env variables (8)
Audited by: codex View Audit History →
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APA citation
Awais68. (2026). context7-integration security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/awais68-context7-integration/audits/9BibTeX citation
@techreport{awais68-awais68-context7-integration-2026,
author = {Awais68},
title = {context7-integration security audit report (audit version 9)},
institution = {Skillstore},
year = {2026},
number = {9},
url = {https://skillstore.io/skills/awais68-context7-integration/audits/9},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "context7-integration security audit report (audit version 9)"
version: "unspecified"
type: report
authors:
- name: "Awais68"
date-released: "2026-07-05"
url: "https://skillstore.io/skills/awais68-context7-integration/audits/9"
identifiers:
- type: other
value: "skillstore:awais68-context7-integration:audit:9"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: Medium 45
Architecture
85
Maintainability
87
Content
70
Community
74
Spec Compliance
What You Can Build
Add Knowledge Search to FastAPI
Implement backend endpoints that ingest documents and return scoped search results for an application.
Ground Chat Answers in Approved Documents
Retrieve policy, FAQ, or procedure content before an AI assistant answers user questions.
Organize Tenant-Specific Knowledge
Model document metadata so each school or organization receives only relevant content.
Try These Prompts
Plan a Basic Context7 Setup
Create a simple Context7 integration plan for my app. Include client setup, required environment variables, and one search endpoint.
Add Scoped Search
Design a Context7 search flow that filters documents by user role and school ID. Include validation and error handling steps.
Design Document Ingestion
Create an ingestion workflow for policy and FAQ documents. Include metadata, batching, retry behavior, and review requirements before upload.
Audit Retrieval Safety
Review a Context7 RAG design for prompt injection, overbroad access, secret handling, and external data transfer risks.
Best Practices
- Review documents for sensitive data before ingestion.
- Use explicit role and tenant metadata for every document.
- Treat retrieved document text as untrusted context in AI prompts.
Avoid
- Do not default sensitive documents to all roles.
- Do not send private documents to an unverified Context7 endpoint.
- Do not paste retrieved content into prompts without instruction boundaries.
Frequently Asked Questions
What does this skill help build?
It helps build Context7 document ingestion, semantic search, and context retrieval flows for application features.
Does it include a complete working package?
No. It provides implementation patterns and code examples that must be adapted to your project.
Which AI tools can use this skill?
The report marks it as compatible with Claude, Codex, and Claude Code.
Does it handle access control?
It shows role and tenant filters, but projects must enforce least privilege and test those filters.
Does it require network access?
Yes. The client examples send requests to a Context7 API endpoint.
What should teams review before use?
Review API key handling, endpoint allowlisting, sensitive document ingestion, and prompt-injection controls.
Developer Details
Author
Awais68License
MIT
Skillstore revision
r1
Version notice
The author did not declare a version.
Ref
5ab1d37e83436c6eef84de88573e142b94f2a4ad
Maintenance freshness
7/20/2026
Usage
7 downloads · 217 views