Neo is a specialised AI/ML engineering agent that can be accessed via an MCP server inside Claude Code.
Claude code is great at software engineering but when it comes to iterative AI tasks that require long horizon experimentation and results may not come in one go, Claude limits exhaust very fast.
The crux is:
We shouldn't let Claude babysit long AI workflows!
These tasks are inherently iterative and can consume hundreds of turns.
With Neo MCP, Claude Code becomes the orchestrator and Neo heavy-lifts complex AI tasks and provides direct status updates with execution logs to Claude running locally in your environment.
This way, Claude spends way less tokens and also Neo consumes upto 62% lower cost compared to direct Claude API usage, thus delivering outcomes as a combined team at way cheaper costs.
This has been our cheat code since last month and we think there is a lot of scope even now to further optimize and mature Neo.
I remember when there was hype around GLM 5 reaching great heights on benchmarks but eventually failing on practical coding and reasoning tasks. I guess this time the hype is real.
The data leaving AWS boundary kills this for any regulated workload. We've been running side-by-side evals of open models against Claude on private test suites, using Neo as the orchestration layer. Keeps everything in-house and gives us objective comparison data.
Five of the top 10 AI repos on GitHub trending this week are "skills" packs for Claude Code. The label is doing wildly different work across them.
forrestchang/andrej-karpathy-skills (~70k stars). One CLAUDE.md file, four behavioral rules, derived from Karpathy's January tweet about agent coding failure modes (silent wrong assumptions, over-complication, not surfacing tradeoffs). Karpathy didn't write the file or endorse it. The README has had a typo in the install command (andrej-karpthy-skills, missing the second "a") since launch. A second repo, multica-ai/andrej-karpathy-skills, is trending in parallel with the same content republished.
mattpocock/skills (~115k stars). Matt Pocock's personal .claude/skills/ folder, published. About 10 small SKILL.md files: tdd, to-issues, to-prd, triage, zoom-out, setup-matt-pocock-skills. Each one is a self-contained markdown prompt with YAML frontmatter declaring when it should auto-fire. Third-party writeups describe it as a reference implementation of Anthropic's SKILL.md format.
affaan-m/everything-claude-code (~175k stars; plus a second repo affaan-m/ECC at ~205k stars which is the same project under a renamed identifier). 48 agent definitions, 182 SKILL.md files, 68 legacy slash-command shims, hooks, rules, MCP configurations, npm packages (ecc-universal, ecc-agentshield), a Tkinter desktop dashboard, and a security scanner (1282 tests, 102 static analysis rules). Includes per-harness adapters for Claude Code, Codex CLI, Codex macOS app, Cursor, OpenCode, Gemini CLI, and Antigravity. Anthropic hackathon winner.
Three orders of magnitude in scope under one word.
What's underneath is Anthropic's SKILL.md format: markdown with YAML frontmatter, auto-loaded at session start. The frontmatter declares when the skill should fire; the harness picks relevant skills based on the description and injects only those into context. It's RAG-over-prompts using model-based routing on descriptions rather than vector stores. The format works well enough that you can mix skills from different authors in the same .claude/ folder without the harness caring, which is the actual reason this took off. Trending packs ship per-harness adapters on top of that substrate so the same skill content installs into Codex, Cursor, OpenCode, etc., with per-harness rewrites.
The trending list is measuring three different things under one label: small high-leverage CLAUDE.md edits (karpathy-skills, cost-to-try wins), curated personal reference sets (mattpocock, distribution-by-reputation wins), and full framework distributions (ECC, comprehensive-catalog-marketing wins). Stars are not telling us which of these are surviving on actual reuse.
The defensibility implications are uncomfortable. When a startup pitches "our agent does X better because of our prompting and workflow," and the artifact is a folder of markdown files with YAML frontmatter, that's a Notion template, not a moat. Karpathy's four rules will be absorbed into the default behavior of the next Claude release. mattpocock's TDD skill is sharp but copyable. ECC's 182-skill catalog is impressive engineering, but the prompts inside can be diffed and ported in an afternoon.
What does seem to hold value after reading these: harness ergonomics (install paths, hook plumbing, cross-tool sync scripts, MCP-server lifecycle), distribution (mattpocock-the-person is a moat, the markdown isn't), and security tooling around skill files specifically (AgentShield, ECC's scanner, is a real product even if the skills it scans aren't). None of those are the prompt.