Borrowing it
Nothing to install: this file belongs to Cogni-AI-OU/vastai-host-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Cogni-AI-OU/vastai-host-mcp/main/.github/skills/context-aware-ops/SKILL.mdgit clone --depth 1 https://github.com/Cogni-AI-OU/vastai-host-mcpWrote 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/cogni-ai-ou/vastai-host-mcp/context-aware-ops)<a href="https://agentmods.dev/skills/cogni-ai-ou/vastai-host-mcp/context-aware-ops"><img src="https://agentmods.dev/badge/skills/cogni-ai-ou/vastai-host-mcp/context-aware-ops/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/cogni-ai-ou/vastai-host-mcp/context-aware-ops"><img src="https://agentmods.dev/badge/skills/cogni-ai-ou/vastai-host-mcp/context-aware-ops.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 | $0.00018 | $0.02379 |
| Opus 5 | $0.00009 | $0.01189 |
| Sonnet 5 | $0.00004 | $0.00476 |
| Haiku 4.5 | $0.00002 | $0.00238 |
Grade A, and why
context-aware-ops 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 10d 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 — 373 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context-Aware Operations Skill
This skill provides patterns and techniques for managing large files and command outputs efficiently, preventing context window exhaustion while maintaining effective problem-solving capabilities.
When to Use This Skill
- Before reading any file in the codebase
- Before executing commands that might produce large output
- When working with logs, build outputs, or data files
- When searching through codebases
- When debugging issues that might involve large resources
Core Principle
Always check before you dump!
Never blindly dump large resources into your context. Always:
- Check the size first
- Use filtering if needed
- Focus on relevant portions only
File Size Checking
Check Line Count
# Fast line count
wc -l filename.txt
# Line count without filename
wc -l < filename.txt
# Line count with human-readable file size
wc -l filename.txt && ls -lh filename.txt
Check File Size
# Human-readable size
ls -lh filename.txt
# Size in bytes (Linux)
stat -c%s filename.txt
# Size in bytes (macOS)
stat -f%z filename.txt
# Quick check if file is large
[ $(wc -l < filename.txt) -gt 500 ] && echo "Large file" || echo "Small file"
Filtered File Reading
Read Beginning and End
# First 50 lines
head -n 50 filename.txt
# Last 50 lines
tail -n 50 filename.txt
# Both ends with separator
head -n 30 filename.txt && echo "..." && tail -n 30 filename.txt
Read Specific Ranges
# Lines 100-200
sed -n '100,200p' filename.txt
# Around a specific line (line 150 ± 25 lines)
sed -n '125,175p' filename.txt
# Skip first N lines, show next M
tail -n +100 filename.txt | head -n 50
Search-Based Reading
# Find and show context
grep -n "pattern" filename.txt
# Show matching lines with 5 lines of context
grep -C 5 "pattern" filename.txt
# Show matching lines with line numbers
grep -n "pattern" filename.txt | head -20
# Count matches without showing content
grep -c "pattern" filename.txt
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.
- 10d ago First seen · 373 lines · 18 tokens per session scan A ef00fd4f889f
context-aware-ops is a skill published in the GitHub repository Cogni-AI-OU/vastai-host-mcp (0 stars, last pushed 5mo ago), licensed MIT. It adds 18 tokens to every session and 2,379 once invoked, about $0.0001 per session on Opus 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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