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 navendubrajesh/context-management-for-agents --skill cursor-context-architecturegit clone --depth 1 https://github.com/navendubrajesh/context-management-for-agentsWrote 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/navendubrajesh/context-management-for-agents/cursor-context-architecture)<a href="https://agentmods.dev/skills/navendubrajesh/context-management-for-agents/cursor-context-architecture"><img src="https://agentmods.dev/badge/skills/navendubrajesh/context-management-for-agents/cursor-context-architecture/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/navendubrajesh/context-management-for-agents/cursor-context-architecture"><img src="https://agentmods.dev/badge/skills/navendubrajesh/context-management-for-agents/cursor-context-architecture.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 | $0.00086 | $0.01167 |
| Opus 5 | $0.00043 | $0.00583 |
| Sonnet 5 | $0.00017 | $0.00233 |
| Haiku 4.5 | $0.00009 | $0.00117 |
Grade A, and why
cursor-context-architecture 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 11d 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cursor Context Architecture
Cursor's context system combines automatic codebase indexing, user-selected @ attachments, project/user/team rules, and agent tool chains into a single fixed-size context window. Unlike inline-tab completion systems, Cursor Agent actively searches, reads, and compresses — but every component competes for the same token budget.
When to Activate
Activate this skill when:
- Diagnosing why Cursor Agent cannot find relevant code despite it existing in the repo
- Understanding what @-mentions, rules, MCP servers, and skills cost in the context ring
- Tuning
.cursorignore/.cursorindexingignorefor indexing vs access control - Deciding when to use @ files vs letting Agent search autonomously
- Evaluating Max mode or large-context models against effective usable capacity
Do not activate this skill for adjacent work owned by other skills:
- Do not activate for platform-agnostic attention mechanics:
context-fundamentals. - Do not activate for writing or restructuring
.mdcrules:cursor-customization. - Do not activate for long-session compaction tactics:
cursor-session-management. - Do not activate for building external RAG pipelines:
memory-systems.
Core Concepts
Codebase semantic indexing
Cursor indexes open workspaces into vector embeddings using a custom embedding model. Code is chunked at meaningful boundaries (functions, classes, logical blocks), embedded, and stored in a vector database. Indexing starts on workspace open; semantic search becomes available at ~80% index completion and syncs changed files every ~5 minutes.
Practical lever: semantic search + grep together outperform grep alone on large codebases (Cursor reports ~12.5% accuracy improvement on 1000+ file repos). Agent chains semantic search → grep → file reads without the user choosing tools.
@-mention context channel
Typing @ attaches explicit context: files/folders, indexed docs, terminal output, past chats, git diffs, browser state. @ mentions are the highest-precision lever when the relevant files are known; skip them when scope is unclear and let Agent search.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 81 lines · 86 tokens per session scan A 8eee5c8325ab
cursor-context-architecture is a skill published in the GitHub repository navendubrajesh/context-management-for-agents (2 stars, last pushed 2mo ago), licensed MIT. It adds 86 tokens to every session and 1,167 once invoked, about $0.0004 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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