Borrowing it
Nothing to install: this file belongs to OussemaBenAmeur/lesson. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/OussemaBenAmeur/lesson/main/CLAUDE.mdgit clone --depth 1 https://github.com/OussemaBenAmeur/lessonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/oussemabenameur/lesson/claude-md)<a href="https://agentmods.dev/instructions/oussemabenameur/lesson/claude-md"><img src="https://agentmods.dev/badge/instructions/oussemabenameur/lesson/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/oussemabenameur/lesson/claude-md"><img src="https://agentmods.dev/badge/instructions/oussemabenameur/lesson/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01569 | $0.01569 |
| Opus 5.5 | $0.00628 | $0.00628 |
| Sonnet 5.5 | $0.00314 | $0.00314 |
| Haiku 4.5 | $0.00157 | $0.00157 |
Grade A, and why
lesson CLAUDE.md 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
lesson — AI Context
A Claude Code plugin that models the learner, not the session.
It watches how someone works, notices what they keep working around without ever learning, and writes them a proper lesson on one of those things — built from the ground up, never stacking jargon on jargon.
Rewritten from scratch on 2026-08-16. The previous design (v0.3, tag
v0.3-graph-era) built a per-session knowledge graph from tool-call logs. It could not work: nothing in it ever created aconceptorhypothesisnode, so root-cause and misconception detection always returned nothing, and the shipping behaviour was an LLM reading a truncated tool log. Do not reintroduce per-session graphs, TF-IDF significance scoring, orarc.jsonl.
The model
Three layers, kept separate:
One knowledge graph is the entire memory. ~/.claude/lesson/graph.json.
Dots are things a person can understand; arrows mean "you need this first".
Every claim carries evidence, an observed/guessed tag, and provenance back
to the session it came from. Schema: docs/knowledge-graph.md.
There is no fixed concept list. Concepts are infinite; any list we shipped
would just be a list of things we thought of. The graph starts empty and grows
via the match-first rule: before adding a node, read the existing nodes
(titles and also_called) and reuse one if it fits. Skip that step and the
same gap becomes five one-off nodes that never accumulate into anything.
Global and always-on. Not per-project. There is no session start/stop
ritual, no active-session marker, no .claude/lessons/ inside target repos.
All state lives in ~/.claude/lesson/.
Depth, not binary. Every concept sits at unknown → aware → working →
mechanistic. A lesson moves one concept up exactly one rung. This is how the
same short concept list serves a beginner and a senior engineer.
Why the concept list exists
So the same gap gets the same name every time. Free-form naming produces "python virtual environments", "conda activation", and "pip inside Dockerfile" as three separate entries with a count of one each — when it is one gap hit three times, and no lesson ever fires.
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.
- 2mo ago First seen · 130 lines · 1,569 tokens per session scan A 2c83068150c0
lesson CLAUDE.md is an instructions file published in the GitHub repository OussemaBenAmeur/lesson (3 stars, last pushed 2mo ago), licensed MIT. It adds 1,569 tokens to every session, about $0.0063 per session on Opus 5.5. 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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