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 xuansenpa1/skillrevise --skill lean4-memoriesgit clone --depth 1 https://github.com/xuansenpa1/skillreviseWrote 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/xuansenpa1/skillrevise/lean4-memories)<a href="https://agentmods.dev/skills/xuansenpa1/skillrevise/lean4-memories"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/lean4-memories/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/xuansenpa1/skillrevise/lean4-memories"><img src="https://agentmods.dev/badge/skills/xuansenpa1/skillrevise/lean4-memories.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 | $0.00045 | $0.02966 |
| Opus 5 | $0.00023 | $0.01483 |
| Sonnet 5 | $0.00009 | $0.00593 |
| Haiku 4.5 | $0.00005 | $0.00297 |
Grade A, and why
lean4-memories 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 8d 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.
This is a copy
100% identical to lean4-memories — 2 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.
How it starts
The opening of the file, as written. The whole thing — 444 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lean 4 Memories
Overview
This skill enables persistent learning and knowledge accumulation across Lean 4 formalization sessions by leveraging MCP (Model Context Protocol) memory servers. It transforms stateless proof assistance into a learning system that remembers successful patterns, avoids known dead-ends, and adapts to project-specific conventions.
Core principle: Learn from each proof session and apply accumulated knowledge to accelerate future work.
When to Use This Skill
This skill applies when working on Lean 4 formalization projects, especially:
- Multi-session projects - Long-running formalizations spanning days/weeks/months
- Repeated proof patterns - Similar theorems requiring similar approaches
- Complex proofs - Theorems with multiple attempted approaches
- Team projects - Shared knowledge across multiple developers
- Learning workflows - Building up domain-specific proof expertise
Especially important when:
- Starting a new session on an existing project
- Encountering a proof pattern similar to previous work
- Trying an approach that previously failed
- Needing to recall project-specific conventions
- Building on successful proof strategies from earlier sessions
How Memory Integration Works
Memory Scoping
All memories are scoped by:
- Project path - Prevents cross-project contamination
- Skill context - Memories tagged with
lean4-memories - Entity type - Structured by pattern type (ProofPattern, FailedApproach, etc.)
Example scoping:
Project: /path/to/lean4/project
Skill: lean4-memories
Entity: ProofPattern:condExp_unique_pattern
Memory Types
1. ProofPattern - Successful proof strategies
Store when: Proof completes successfully after exploration
Retrieve when: Similar goal pattern detected
2. FailedApproach - Known dead-ends to avoid
Store when: Approach attempted but failed/looped/errored
Retrieve when: About to try similar approach
3. ProjectConvention - Code style and patterns
Store when: Consistent pattern observed (naming, structure, tactics)
Retrieve when: Creating new definitions/theorems
What ships with it
2 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.
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.
- 8d ago First seen · 444 lines · 45 tokens per session scan A fb0e50ea8bc6
lean4-memories is a skill published in the GitHub repository xuansenpa1/skillrevise (56 stars, last pushed 6d ago), licensed MIT. It adds 45 tokens to every session and 2,966 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to lean4-memories, differing in 2 lines, and is treated as a copy.
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