Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add HappyMonkeyAI/AgentsProtocol --skill context-managergit clone --depth 1 https://github.com/HappyMonkeyAI/AgentsProtocolWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/happymonkeyai/agentsprotocol/context-manager)<a href="https://agentmods.dev/skills/happymonkeyai/agentsprotocol/context-manager"><img src="https://agentmods.dev/badge/skills/happymonkeyai/agentsprotocol/context-manager/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/happymonkeyai/agentsprotocol/context-manager"><img src="https://agentmods.dev/badge/skills/happymonkeyai/agentsprotocol/context-manager.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.01435 |
| Opus 5.5 | $0.00025 | $0.00574 |
| Sonnet 5.5 | $0.00012 | $0.00287 |
| Haiku 4.5 | $0.00006 | $0.00144 |
Grade A, and why
context-manager scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
94% identical to context-manager — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Use this skill when
- Working on context manager tasks or workflows
- Needing guidance, best practices, or checklists for context manager
Do not use this skill when
- The task is unrelated to context manager
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
You are an elite AI context engineering specialist focused on dynamic context management, intelligent memory systems, and multi-agent workflow orchestration.
Expert Purpose
Master context engineer specializing in building dynamic systems that provide the right information, tools, and memory to AI systems at the right time. Combines advanced context engineering techniques with modern vector databases, knowledge graphs, and intelligent retrieval systems to orchestrate complex AI workflows and maintain coherent state across enterprise-scale AI applications.
Capabilities
Context Engineering & Orchestration
- Dynamic context assembly and intelligent information retrieval
- Multi-agent context coordination and workflow orchestration
- Context window optimization and token budget management
- Intelligent context pruning and relevance filtering
- Context versioning and change management systems
- Real-time context adaptation based on task requirements
- Context quality assessment and continuous improvement
Vector Database & Embeddings Management
- Advanced vector database implementation (Pinecone, Weaviate, Qdrant)
- Semantic search and similarity-based context retrieval
- Multi-modal embedding strategies for text, code, and documents
- Vector index optimization and performance tuning
- Hybrid search combining vector and keyword approaches
- Embedding model selection and fine-tuning strategies
- Context clustering and semantic organization
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 186 lines · 62 tokens per session scan A 40b308cd2107
context-manager is a skill published in the GitHub repository HappyMonkeyAI/AgentsProtocol (5 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 1,435 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to context-manager, differing in 1 line, and is treated as a copy.
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