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 agentmods add rules/phanindra208/universal-context-mode/context-modegit clone --depth 1 https://github.com/Phanindra208/universal-context-modeWhat 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 | $0.00352 | $0.00352 |
| Opus 5 | $0.00176 | $0.00176 |
| Sonnet 5 | $0.00070 | $0.00070 |
| Haiku 4.5 | $0.00035 | $0.00035 |
Grade A, and why
context-mode 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 yesterday.
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.
What it actually says
Context Preservation Rules
When executing commands that may produce large output (>5KB), use the context-mode MCP tools:
- Instead of running shell commands directly, use
context-mode.executewithlanguage: "shell" - Instead of reading large files, use
context-mode.execute_file - When fetching documentation, use
context-mode.fetch_and_index+context-mode.search - For any tool returning large output, use
context-mode.compress
Commands likely to produce large output
git log,git diff,catlarge files,find, reading log filesnpm list,pip list, dependency audits,yarn why- API responses, test suite output (>100 tests)
- Browser snapshots, web page content, database dumps
Example usage
// Instead of: bash("git log --oneline -50")
execute({ language: "shell", code: "git log --oneline -50", intent: "recent changes" })
// Instead of: read_file("package-lock.json")
execute_file({
file_path: "package-lock.json",
code: "const d=JSON.parse(process.env.FILE_CONTENT); console.log('Packages:', Object.keys(d.dependencies||{}).length)"
})
// Compress any large text
compress({ content: largeOutput, intent: "find error messages" })
// Fetch and index docs
fetch_and_index({ url: "https://docs.example.com" })
search({ query: "what I need to know" })
// Check how much context was saved this session report()
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.
- yesterday First seen · 44 lines · 352 tokens per session scan A a2326c1d6ddc
context-mode is a cursor rule published in the GitHub repository Phanindra208/universal-context-mode (5 stars, last pushed 5mo ago), licensed MIT. It adds 352 tokens to every session, about $0.0018 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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