lessons

lessons is a command for Claude Code from christopherlouet/claude-base. It costs 0 tokens per session (1,252 once invoked), scanned A, original, MIT.

A command that lists feedback-based rules and preferences already recorded for a project or across projects. These entries are lessons captured from user corrections.

In plain words
What is it for?
Viewing or filtering recorded lessons, promoting a newly learned rule, importing existing memories or pruning the personal lessons store.
Why use it?
It helps the agent or developer see known mistakes and preferences so they can avoid repeating them.

Command 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 commands/christopherlouet/claude-base/lessons
Clone the repo
git clone --depth 1 https://github.com/christopherlouet/claude-base

Made for: Claude Code.

Wrote 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.

agentmods badge for lessons

README.md
[![agentmods](https://agentmods.dev/badge/commands/christopherlouet/claude-base/lessons.svg)](https://agentmods.dev/commands/christopherlouet/claude-base/lessons)
Your own site
<a href="https://agentmods.dev/commands/christopherlouet/claude-base/lessons"><img src="https://agentmods.dev/badge/commands/christopherlouet/claude-base/lessons.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,252 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 $0.00000 $0.01252
Opus 5 $0.00000 $0.00626
Sonnet 5 $0.00000 $0.00250
Haiku 4.5 $0.00000 $0.00125

Measured yesterday against content hash ece410322b1f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lessons 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.

.claude/commands/lessons.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

LESSONS Command

Lists the feedback memories captured for the current project (and globally) — the "lessons" learned from user corrections.

Context

$ARGUMENTS

Objective

Provide an overview of the self-improvement system: which rules, counter-examples, or preferences have already been recorded to avoid repeating the same mistakes.

Usage

/lessons              # List all feedback memories for the project (read-only)
/lessons <keyword>    # Filter by keyword (e.g., /lessons test, /lessons git)
/lessons --promote    # Capture the lesson just learned into the personal store
/lessons --bootstrap  # One-off: backfill the personal store from existing memories
/lessons --prune      # Keep the personal store under its size budget

The --promote, --bootstrap, and --prune modes feed the personal cross-project lessons store at ~/.claude/rules/lessons.md (loaded into every project by Claude Code). They follow the self-improvement rule: every write is generalized + sanitized + human-confirmed, and the lessons are personal — never committed to any repo.

Modes

--promote (explicit capture — fallback to the reflex)

For when the in-conversation reflex didn't fire but you want to keep a lesson:

  1. Take the lesson just learned, generalize it to a one-line principle and sanitize it (strip project/company/person names, paths, URLs, identifiers, verbatim snippets, secrets).
  2. Check for recurrence — the store is in your context. If the same principle is already stored, propose bumping its (seen N times) marker instead of adding a duplicate ((seen 2 times) on the first repeat, then N+1).
  3. Show it and ask the user to keep / edit / discard (or confirm the bump).
  4. On confirmation, write to ~/.claude/rules/lessons.md (create if absent): append the new lesson as a - bullet under its matching ## Topic heading (create the heading if none fits), or apply the recurrence bump. If it can't be generalized, keep it as a local project memory instead.

Read the full file on GitHub · 117 lines

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 · 117 lines · 0 tokens per session scan A ece410322b1f

Subscribe to this mod's changes

lessons is a command published in the GitHub repository christopherlouet/claude-base (5 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,252 tokens. 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 2026-09-03.