self_evolve_rag

self_evolve_rag is a skill for Claude Code, Codex from Leeroo-AI/leeroopedia-mcp. It costs 0 tokens per session (555 once invoked), scanned A, original, MIT.

A reference for using Leeroopedia knowledge-base tools in a self-evolving RAG project. RAG means finding relevant stored documents before generating an answer.

In plain words
What is it for?
Use it for guidance on document chunking, retrieval methods, score fusion, parameter choices, atomic updates, and troubleshooting in that project.
Why use it?
It explains when to consult the knowledge base and reminds developers to check its advice against actual search results.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for guidance on document chunking, retrieval methods, score fusion, parameter choices, atomic updates, and troubleshooting in that project.

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Install with agentmods
npx agentmods add skills/leeroo-ai/leeroopedia-mcp/self_evolve_rag
Install

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.

Any agent
npx skills add Leeroo-AI/leeroopedia-mcp --skill self_evolve_rag
Clone the repo
git clone --depth 1 https://github.com/Leeroo-AI/leeroopedia-mcp

Made for: Claude Code, Codex.

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 self_evolve_rag

README.md
[![agentmods](https://agentmods.dev/badge/skills/leeroo-ai/leeroopedia-mcp/self_evolve_rag/github.svg)](https://agentmods.dev/skills/leeroo-ai/leeroopedia-mcp/self_evolve_rag)
Your own site
<a href="https://agentmods.dev/skills/leeroo-ai/leeroopedia-mcp/self_evolve_rag"><img src="https://agentmods.dev/badge/skills/leeroo-ai/leeroopedia-mcp/self_evolve_rag/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.

agentmods 80×15 button for self_evolve_rag

Your own site · 80×15
<a href="https://agentmods.dev/skills/leeroo-ai/leeroopedia-mcp/self_evolve_rag"><img src="https://agentmods.dev/badge/skills/leeroo-ai/leeroopedia-mcp/self_evolve_rag.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 555 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 original No closer match found 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 $0.00000 $0.00555
Opus 5 $0.00000 $0.00278
Sonnet 5 $0.00000 $0.00111
Haiku 4.5 $0.00000 $0.00056

Measured 11d ago against content hash 389e50c70ac7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

self_evolve_rag 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.

The scan reads SKILL.md. This mod also ships 3 executable files (eval_harness.py, generate_benchmarks.py, run_benchmark.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

examples/self_evolve_rag/SKILL.md · 34 lines

How it starts

The opening of the file, as written. The whole thing — 34 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Leeroopedia Knowledge Base Tools — Reference

This document describes how to use the Leeroopedia MCP tools for the Self-Evolving RAG task. It is kept as a reference and is NOT included in the agent prompt.


Leeroopedia Knowledge Base Tools

You have access to the Leeroopedia MCP tools. Use them to learn implementation patterns, but ALWAYS validate KB recommendations against your actual empirical results. The KB provides general best practices — your specific corpus (IBM TechQA) may behave differently.

When to use KB tools:

  • At the START of each phase, to learn implementation patterns (chunking strategies, atomic swap patterns, hybrid retrieval fusion methods).
  • When you encounter a BUG or ERROR you cannot resolve from code alone.
  • When you need to verify correctness of a specific algorithm (e.g., score normalization formula).

When NOT to use KB tools:

  • Do NOT use KB recommendations to override empirical results. If your data shows BM25 outperforms vector search, trust your data — even if the KB suggests semantic search is generally superior.
  • Do NOT use query_hyperparameter_priors to set initial fusion weights or chunk sizes. Use the defaults specified in this proposal (0.5/0.5 weights, 512-token chunks) and let the evolution loop adapt based on actual metrics.
  • Do NOT use KB recommendations to decide how many documents to re-chunk. The diagnosis logic should determine scope based on failure analysis, not KB heuristics.

Tool-specific guidance:

  • search_knowledge: Use to look up implementation patterns (atomic index swaps, hybrid retrieval fusion, chunking strategies). Focus on HOW to implement correctly, not WHAT hyperparameters to use.

  • build_plan: Use ONCE at the start to get a high-level implementation skeleton. Do not request plans for individual evolution rounds — the evolution logic should be data-driven, not plan-driven.

  • verify_code_math: Use to verify correctness of score normalization, metric computation, and atomic swap logic. This is the highest-value tool — use it after writing critical code sections.

Read the full file on GitHub · 34 lines

Files

What ships with it

6 files 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.

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. 11d ago First seen · 34 lines · 0 tokens per session scan A 389e50c70ac7

Subscribe to this mod's changes

self_evolve_rag is a skill published in the GitHub repository Leeroo-AI/leeroopedia-mcp (14 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 555 tokens. 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 2026-08-30.