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react-agent-pattern: Skill for Cursor

.cursor/skills/rag-governance/SKILL.md

rag-governance is a skill for Cursor from vpeetla-ai/react-agent-pattern. It costs 54 tokens per session (292 once invoked), scanned A, a copy of rag-governance, MIT.

A set of rules and implementation guidance for retrieval-augmented generation (RAG), where an AI answers using searched documents. It covers access checks, combined keyword and meaning-based search, result reordering, citations, and human review for sensitive results.

In plain words
What is it for?
Use it when building or tuning enterprise document search, connecting a Qdrant database, setting retrieval parameters, or testing that restricted passages are not returned.
Why use it?
It helps prevent answers from using documents a person should not see and makes it possible to trace answers back to source passages.

Skill for Cursor

Written for Cursor: installed under .cursor/.

This is vpeetla-ai/react-agent-pattern's own configuration. It tells Cursor how to work on react-agent-pattern itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything react-agent-pattern configures →

not rated 2repo 2mo ago A scan 54 tokens copy · 100% MIT
View source ↗ vpeetla-ai/react-agent-pattern react-agent-pattern.vercel.app
Reuse

Borrowing it

Nothing to install: this file belongs to vpeetla-ai/react-agent-pattern. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/vpeetla-ai/react-agent-pattern/main/.cursor/skills/rag-governance/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/vpeetla-ai/react-agent-pattern

Made for: Cursor.

Wrote 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.

agentmods badge for rag-governance

README.md
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Your own site
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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.

agentmods 80×15 button for rag-governance

Your own site · 80×15
<a href="https://agentmods.dev/skills/vpeetla-ai/react-agent-pattern/rag-governance"><img src="https://agentmods.dev/badge/skills/vpeetla-ai/react-agent-pattern/rag-governance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 292 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.00292
Opus 5.5 $0.00022 $0.00117
Sonnet 5.5 $0.00011 $0.00058
Haiku 4.5 $0.00005 $0.00029

Measured 2mo ago against content hash 4cd65b7adc6f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

rag-governance 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 2mo 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.

Origin

This is a copy

100% identical to rag-governance — 0 lines 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.

.cursor/skills/rag-governance/SKILL.md · 42 lines

What it actually says

RAG Governance

Principles

  1. Access before ranking — filter by tenant/role before vector search
  2. Citations required — every answer cites chunk IDs
  3. HITL for sensitive — low confidence or PII-tagged chunks → gateway pause

Hybrid retrieval

query → embed → vector + BM25 → merge (hybrid_alpha) → rerank → top_k

VAP strategy adapter

  • enterprise_rag strategy in venkat-ai-platform delegates to Enterprise RAG API
  • Env: ENTERPRISE_RAG_API_URL

LoopForge tuning (ODAEU)

  • top_k, hybrid_alpha, rerank_threshold versioned in RAG config tree
  • Lessons stored when eval fails

Reference

  • enterprise_rag_platform — Qdrant adapter, OTLP export
  • loop-engine-agent-platform/src/loop_engine/rag/

Tests

  • Golden queries with expected chunk IDs
  • Access denial: user without role gets empty retrieval, not leaked chunks
Changes

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.

  1. 2mo ago First seen · 42 lines · 54 tokens per session scan A 4cd65b7adc6f

Subscribe to this mod's changes

rag-governance is a skill published in the GitHub repository vpeetla-ai/react-agent-pattern (2 stars, last pushed 2mo ago), licensed MIT. It adds 54 tokens to every session and 292 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to rag-governance, differing in 0 lines, and is treated as a copy.

Data and AIPythonai-agentslanggraphreact-agenttutorial
Related

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rag-governance next to 6 skills from other repositories
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