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 gitstq/awesome-ai-agent-skills --skill context-mastergit clone --depth 1 https://github.com/gitstq/awesome-ai-agent-skillsWrote 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/gitstq/awesome-ai-agent-skills/context-master)<a href="https://agentmods.dev/skills/gitstq/awesome-ai-agent-skills/context-master"><img src="https://agentmods.dev/badge/skills/gitstq/awesome-ai-agent-skills/context-master/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/gitstq/awesome-ai-agent-skills/context-master"><img src="https://agentmods.dev/badge/skills/gitstq/awesome-ai-agent-skills/context-master.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 | $0.00142 | $0.02056 |
| Opus 5.5 | $0.00057 | $0.00822 |
| Sonnet 5.5 | $0.00028 | $0.00411 |
| Haiku 4.5 | $0.00014 | $0.00206 |
Grade A, and why
context-master 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.
How it starts
The opening of the file, as written. The whole thing — 246 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Master - Intelligent Context Management System
Stop losing context in long coding sessions. Let Context Master manage your AI's memory intelligently.
The Problem
Every AI coding agent has a context window limit. When conversations get long or codebases are large:
- The agent "forgets" earlier instructions
- Important decisions get lost in the noise
- Repetitive information wastes precious context
- The agent starts giving contradictory answers
Context Master solves this with a smart, tiered context management system.
Core Architecture
Three-Tier Context Model
┌─────────────────────────────────────────────┐
│ TIER 1: HOT CONTEXT (Always Loaded) │
│ - Current task description │
│ - Active file contents │
│ - Recent decisions (last 10) │
│ - User preferences │
│ Budget: 30% of context window │
├─────────────────────────────────────────────┤
│ TIER 2: WARM CONTEXT (Loaded on Demand) │
│ - Related file summaries │
│ - Architecture decisions │
│ - Error history & fixes │
│ Budget: 40% of context window │
├─────────────────────────────────────────────┤
│ TIER 3: COLD CONTEXT (Archived) │
│ - Old conversation summaries │
│ - Historical decisions │
│ - Resolved issues │
│ Accessed via semantic search │
│ Budget: 30% of context window │
└─────────────────────────────────────────────┘
Smart Features
1. Automatic Context Budget
The skill calculates optimal context allocation based on:
- Model context window size (128K, 200K, 1M, etc.)
- Current usage level (percentage consumed)
- Task complexity (number of files involved)
- Conversation length (number of turns)
When context reaches 70% capacity, it automatically:
- Summarizes the oldest conversation turns
- Archives resolved decisions
- Compresses redundant information
- Promotes critical info to Tier 1
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 · 246 lines · 142 tokens per session scan A 81afe4fe70f4
context-master is a skill published in the GitHub repository gitstq/awesome-ai-agent-skills (1 stars, last pushed 7mo ago), licensed MIT. It adds 142 tokens to every session and 2,056 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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