project-learner

project-learner is a skill for Claude Code, Codex from sanshan1978/codeguard-rag-mcp. It costs 136 tokens per session (4,720 once invoked), scanned A, original, no licence file.

An interactive coach that teaches you a codebase through interview-style questions and answers. It reads the project’s code and documentation, then tracks your progress.

In plain words
What is it for?
Use it to study a project’s architecture and topics, answer follow-up questions, receive guidance with code references, and save learning progress.
Why use it?
It helps reveal what you understand and what you need to learn instead of leaving you to explore an unfamiliar project alone.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/sanshan1978/codeguard-rag-mcp/project-learner
Any agent
npx skills add sanshan1978/codeguard-rag-mcp --skill project-learner
Clone the repo
git clone --depth 1 https://github.com/sanshan1978/codeguard-rag-mcp

Made for: Claude Code, Codex.

Per session 136 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,720 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00136 $0.04720
Opus 5 $0.00068 $0.02360
Sonnet 5 $0.00027 $0.00944
Haiku 4.5 $0.00014 $0.00472

Measured 2d ago against content hash 85f2083cf478, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

project-learner 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 2d 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.

.github/skills/project-learner/SKILL.md · 358 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

1 file 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. 2d ago First seen · 358 lines · 136 tokens per session scan A 85f2083cf478

Subscribe to this mod's changes

project-learner is a skill published in the GitHub repository sanshan1978/codeguard-rag-mcp (0 stars, last pushed 7d ago), with no licence file. It adds 136 tokens to every session and 4,720 once invoked, about $0.0007 per session on Opus 5. 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 2026-08-31.

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