context-manager
Design Reliable AI Context Systems
AI applications lose relevance when context, memory, and retrieval systems are poorly designed. This skill guides context architecture, RAG, knowledge graphs, and multi-agent state management.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "context-manager" from https://skillstore.io/skills/sickn33-context-manager.md and its manifest at https://skillstore.io/api/skills/sickn33-context-manager/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.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 "context-manager". Design context management for a customer support assistant with long-running cases.
Expected outcome:
Use a compact working summary, retrieve case evidence on demand, store approved durable facts, and log every agent handoff.
Using "context-manager". Improve retrieval quality for a large technical document collection.
Expected outcome:
Test structure-aware chunks, combine semantic and keyword retrieval, rerank candidates, filter stale versions, and measure grounded answer quality.
Using "context-manager". Reduce token use across a multi-agent workflow.
Expected outcome:
Assign context ownership, pass task-specific summaries, retrieve details only when needed, and track token cost per successful workflow.
Security Audit
SafeBoth static findings are false positives. The cited lines contain a Markdown file reference and a hybrid-search capability statement, without shell execution or system reconnaissance. No semantic security issue was found.
Risk Factors
⚙️ External commands (1)
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<iframe src="https://skillstore.io/embed/skills/sickn33-context-manager.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
sickn33. (2026). context-manager security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-context-manager/audits/5BibTeX citation
@techreport{sickn33-sickn33-context-manager-2026,
author = {sickn33},
title = {context-manager security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/sickn33-context-manager/audits/5},
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: "context-manager security audit report (audit version 5)"
version: "unspecified"
type: report
authors:
- name: "sickn33"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/sickn33-context-manager/audits/5"
identifiers:
- type: other
value: "skillstore:sickn33-context-manager:audit:5"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Plan a Support Context Architecture
Design retrieval, memory, and agent handoffs for consistent responses across long-running customer cases.
Improve Enterprise Document Retrieval
Select chunking, embedding, hybrid search, ranking, and freshness strategies for a large internal document collection.
Control Multi-Agent Workflow State
Define context ownership, routing, handoff, and recovery rules for a coordinated AI workflow.
Try These Prompts
Review this AI workflow: [workflow]. Identify required context, missing inputs, token constraints, and a simple assembly strategy.
Design a RAG pipeline for [corpus]. Recommend chunking, embeddings, retrieval, ranking, freshness checks, and evaluation metrics.
Create a memory strategy for [application]. Separate working, episodic, semantic, and persistent memory with retention and retrieval rules.
Architect context management for [agents and workflow]. Define ownership, handoffs, isolation, token budgets, failure recovery, governance, and measurable service targets.
Best Practices
- Define measurable relevance, latency, cost, freshness, and privacy requirements before selecting components.
- Separate durable facts, conversation history, retrieved evidence, and temporary working context.
- Evaluate retrieval and final responses with representative tasks, failure cases, and stale data.
Avoid
- Do not place every available document into each prompt.
- Do not choose an embedding model or vector database without measured requirements.
- Do not store sensitive conversation history without retention, access, and deletion controls.