How to Build a self-improving-agent? 3 Must-Have Skill Sets for Agent Memory, Self-Correction, and Evaluation
From concept to engineering practice · 3 scenarios with 6 real Skills · One command to install
1-second copy command · Agent auto-installs · Free, no quota cost
"Great concept — but landing it is another story"
"We tested self-improving for 6 weeks. Conclusion: the concept is solid, but framework and data feedback are the real performance levers — not 'AI getting smarter on its own'."
— source: rednote · self-improving-agent 6-week test
"The biggest issue isn't how well the agent reflects — it's who provides feedback, what gets updated, and how to prevent drift in this self-evolution loop."
— source: X · Agent self-evolution research notes
"Agent capability gains come not just from stronger base models but from the harness getting stronger. But when the harness starts self-evolving, how do we know the Agent actually improved?"
— source: Reddit · Lilian Weng SEAGym review
These real voices scattered across rednote, X, Reddit, Github... capture the daily reality of AI developers who want to build self-improving agents but don't know where to start. Real self-evolution isn't a magic framework — it's giving your Agent three things: memory, self-correction, and evaluation. Install deep-skill-finder and your Agent will automatically discover Skills matching these capabilities.
Lazy solution · Recommended
Install deep-skill-finder once, let your Agent find Skills itself
The self-improving capabilities you want (persistent memory, self-correction, performance evaluation) — the matching Skills are all on Meyo. You don't need to find them one by one — after installing deep-skill-finder, your Agent will automatically search Meyo's 50000+ Skill library and recommend the ones matching your current task. Just say what you want done; let the Agent handle Skill matching.
Copy command → paste to Claude Code / Codex / Cursor / WorkBuddy · Agent will auto-install:
Install the deep-skill-finder skill: download the skill package from https://www.meyo.life/skill-finder, extract it to your local skill directory and enable it.
Or check out the common scenario Skills below. Want to learn more about deep-skill-finder → meyo.life/skill
3 self-improving-agent Engineering Scenarios · Top 2 Skills Each
Install them all, or pick 1 or 2 by name. Don't worry about installing wrong — they're free, uninstall anytime.
Agent Persistent Memory
Let your Agent remember past mistakes and your preferences
2 Skills with different approaches · pick what fits your scenario · or install both to compare
self-improving-agent-cn
Top 1
For: Agent learns from errors and remembers automatically
Auto-captures errors, user corrections and best practices into long-term memory — solves the same mistakes repeated pain point
23926 installs
For: Cross-session persistent Agent memory
LanceDB-based vectorized long-term memory storage with intent/scene isolation to prevent memory pollution
2649 installs
Agent Self-Correction
Agent detects and fixes its own mistakes
2 Skills with different approaches · pick what fits your scenario · or install both to compare
introspection-debugger
Top 1
For: Agent auto-troubleshoots and repairs its own errors
Gives AI Agent self-diagnosis and auto-repair — error capture, root cause analysis, automated fix and report generation
936 installs
For: Conversational self-correction and intent refinement
Model self-check and correction — re-analyzes intent when user points out errors instead of modifying previous response
632 installs
Agent Performance Benchmarking
How do you know the Agent actually improved? Let data tell
2 Skills with different approaches · pick what fits your scenario · or install both to compare
For: System-level framework for continuous self-optimization
Recursive self-improvement system — auto-detects and fixes errors, supports concurrent execution, automated testing and error prediction
7081 installs
For: Benchmark and score your Agent's capabilities
Professional-grade Agent performance evaluation framework — multi-dimensional automated quantitative assessment and benchmarking
833 installs
Join the deep-skill-finder Discord Community
Connect with other deep-skill-finder users to exchange workflow tips and get installation help
FAQ
Q: Are self-improving-agent and self-evolving-agent the same thing?
A: These two concepts overlap heavily but are not identical. self-improving focuses on "learning from experience and improving," while self-evolving is broader, covering model weights, harness, and external file evolution. For engineers, the implementation path is the same: install memory first, then self-correction, and finally evaluation — three steps give your Agent basic self-evolution capability.
Q: Will these Skills conflict with each other?
A: Memory and correction Skills generally don't conflict — they operate at different stages of the Agent execution pipeline. But evaluation Skills invoke the Agent to run test tasks during execution, so running multiple evaluations simultaneously may impact performance. We recommend installing self-improving-agent-cn first for base memory, then benchclaw for evaluation, and adding self-correction as needed.
Q: I don't use Claude Code, I use Cursor / Codex. Can I still install these Skills?
A: Yes. These Skills are cross-Agent neutral designs — Claude Code, Codex, Cursor, and WorkBuddy all work. The installation is identical: download the package from meyo.life/community/skills, extract it to your Agent's Skill directory, and you're done.
Q: self-improving-agent-cn has 24000+ downloads. What does it actually do?
A: It automatically captures errors during Agent execution, user corrections, and successful experiences, converting them into long-term memory files. Next time the Agent encounters a similar task, it checks memory first to avoid repeating mistakes — this is currently the most mature self-evolution memory Skill in the community.
Q: What does "harness self-evolving" mean?
A: Lilian Weng proposed in Harness Engineering that Agent capability gains come not just from the base model — improvements at the "harness" layer (prompt, memory, tools, workflow) are key. When the harness starts optimizing itself, that's self-improving. The question is: how do you verify the harness actually got better — this is exactly what evaluation Skills like benchclaw solve.
Q: After installing deep-skill-finder, will my Agent automatically find these self-evolution Skills?
A: Yes. After installing deep-skill-finder, you just tell your Agent "help me implement self-improving capability" or "let the Agent learn from mistakes," and deep-skill-finder will automatically search the Meyo Skill library and recommend appropriate memory, correction, and evaluation Skills.