learning-progress

A read-only learning-progress report that summarizes evidence of what a learner can do, what needs review, and what to learn next.

In plain words
What is it for?
Use it to review independent or assisted work, overdue practice, repeated mistakes, and a suitable next step.
Why use it?
It gathers recent learning records into clear categories without changing the learner’s progress data. It also avoids guessing when the available evidence is incomplete.

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/yyz666ai/learning-agent/learning-progress
Any agent
npx skills add yyz666ai/Learning-Agent --skill learning-progress
Clone the repo
git clone --depth 1 https://github.com/yyz666ai/Learning-Agent

Made for: Claude Code, Codex.

Per session 32 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 298 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00032 $0.00298
Opus 5 $0.00016 $0.00149
Sonnet 5 $0.00006 $0.00060
Haiku 4.5 $0.00003 $0.00030

Measured yesterday against content hash bd4ae2e21f02, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

learning-progress 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 yesterday.

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.

workspace/dev/.codex/skills/learning-progress/SKILL.md · 22 lines

What it actually says

学习进度

这是一个严格 read-only 的汇总 Skill。不得更新掌握状态,也不得以汇报为由补写历史证据。

执行流程

  1. 读取热状态、活动计划、活动计划引用的掌握度节点、到期复习摘要和近期相关证据;不得扫描全部历史。
  2. references/progress-contract.md 把证据归入:独立完成辅助完成待复习重复误区推荐下一步
  3. 每个判断都标明证据来源和时间。证据缺失或状态文件无法验证时明确说“不足以判断”,不得估算百分比。
  4. 推荐一个与当前目标和先修关系一致的下一步,但不自动修改计划。

边界

  • 用户提交作业时,路由到 assignment-review,不要在进度汇报中顺便批改。
  • 状态损坏时停止推断,指出具体无法读取的文件和可恢复入口。
  • 本 Skill 不执行任何写操作,包括修复、迁移、刷新时间戳或更新复习日期。
Files

What ships with it

3 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. yesterday First seen · 22 lines · 32 tokens per session scan A bd4ae2e21f02

Subscribe to this mod's changes

learning-progress is a skill published in the GitHub repository yyz666ai/Learning-Agent (1 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 298 once invoked, about $0.0002 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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