learner-profiler

A learner assessment tool that estimates what someone knows, how they prefer to learn, and how accurately their confidence matches their answers. Its knowledge assessment is inspired by item response theory, a method for estimating ability from answers to questions.

In plain words
What is it for?
Use it to assess existing knowledge, identify learning preferences, analyse answer patterns, and find overconfidence or underconfidence.
Why use it?
It provides a starting picture of a learner instead of using the same path for everyone. It can highlight cases where confidence and actual accuracy do not match.

Agent for Claude Code

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 agents/idoforgod/vibe-learning-agenticworkflow/learner-profiler
Clone the repo
git clone --depth 1 https://github.com/idoforgod/Vibe-learning-AgenticWorkflow

Made for: Claude Code.

Per session 32 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,478 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 $0.00032 $0.02478
Opus 5 $0.00016 $0.01239
Sonnet 5 $0.00006 $0.00496
Haiku 4.5 $0.00003 $0.00248

Measured 3d ago against content hash 7a0c6aee2db4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

learner-profiler 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 3d 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.

.claude/agents/learner-profiler.md · 221 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

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. 3d ago First seen · 221 lines · 32 tokens per session scan A 7a0c6aee2db4

Subscribe to this mod's changes

learner-profiler is an agent published in the GitHub repository idoforgod/Vibe-learning-AgenticWorkflow (24 stars, last pushed 6mo ago), with no licence file. It adds 32 tokens to every session and 2,478 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 2026-08-30.

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