review

review is a command for coding agents from gf-labs/ramp. It costs 11 tokens per session (2,529 once invoked), scanned B, original, MIT.

A command for spaced repetition, a study method that brings older material back for review at planned times. It reviews knowledge-graph items that are due for a selected topic.

In plain words
What is it for?
Use it to review due learning items for a topic and handle the first review session when no topic has been started.
Why use it?
It helps you practise stored information regularly instead of relying on one-time reading or memory.

Command

Installs and runs on its own, but its text points at files inside its plugin — anything it tells you to read at a ${CLAUDE_PLUGIN_ROOT} path is only there once the plugin is installed. Installing the plugin gets both.

Part of the ramp plugin — 11 commands, 2 hooks shipped together

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/gf-labs/ramp/review
Clone the repo
git clone --depth 1 https://github.com/gf-labs/ramp

Or install ramp, the plugin that ships this one along with the rest of its 11 commands, 2 hooks.

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 review

README.md
[![agentmods](https://agentmods.dev/badge/commands/gf-labs/ramp/review.svg)](https://agentmods.dev/commands/gf-labs/ramp/review)
Your own site
<a href="https://agentmods.dev/commands/gf-labs/ramp/review"><img src="https://agentmods.dev/badge/commands/gf-labs/ramp/review.svg" alt="Measured on agentmods" height="20"></a>
Per session 11 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,529 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. 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 5.1 $0.00011 $0.02529
Opus 5 $0.00005 $0.01264
Sonnet 5 $0.00002 $0.00506
Haiku 4.5 $0.00001 $0.00253

Measured 5d ago against content hash 97f91ce909be, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-05, from the pricing page.

Security

Grade B, and why

review scanned grade B with 1 finding 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 5d 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

!`FIRST=$(echo "$ARGUMENTS" | awk '{print tolower($1)}'); if [ -n "$FIRST" ] && { [ -f "$HOME/.claude/ramp/schemas/$FIRST.md" ] || [ -f ".claude/knowledge-graphs/schemas/$FIRST.md" ]; }; then TOPIC="$FIRST"; else TOPIC="
commands/review.md · 154 lines

How it starts

The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Context

Requested topic: $ARGUMENTS

Active topic (first word if it matches a known topic, otherwise "claude-code"): !FIRST=$(echo "$ARGUMENTS" | awk '{print tolower($1)}'); if [ -n "$FIRST" ] && { [ -f "$HOME/.claude/ramp/schemas/$FIRST.md" ] || [ -f ".claude/knowledge-graphs/schemas/$FIRST.md" ]; }; then echo "$FIRST"; else echo "claude-code"; fi

Today's date: !date +%Y-%m-%d

Due nodes (kernel-computed SR queue for the active topic — the same rule as every due count ramp shows): !FIRST=$(echo "$ARGUMENTS" | awk '{print tolower($1)}'); if [ -n "$FIRST" ] && { [ -f "$HOME/.claude/ramp/schemas/$FIRST.md" ] || [ -f ".claude/knowledge-graphs/schemas/$FIRST.md" ]; }; then TOPIC="$FIRST"; else TOPIC="claude-code"; fi; python3 "$CLAUDE_PLUGIN_ROOT/ramp_core.py" due "$TOPIC" 2>/dev/null || echo "DUE_UNAVAILABLE"

First-run signal (zero started topics ⇒ redirect a newcomer): !python3 "$CLAUDE_PLUGIN_ROOT/ramp_core.py" catalog 2>/dev/null | python3 -c "import sys,json; c=json.load(sys.stdin); print('FIRST_RUN' if not any(t['started'] for t in c) else 'HAS_GRAPHS')" 2>/dev/null || echo "HAS_GRAPHS"

Knowledge graph contents (for active topic): !FIRST=$(echo "$ARGUMENTS" | awk '{print tolower($1)}'); if [ -n "$FIRST" ] && { [ -f "$HOME/.claude/ramp/schemas/$FIRST.md" ] || [ -f ".claude/knowledge-graphs/schemas/$FIRST.md" ]; }; then TOPIC="$FIRST"; else TOPIC="claude-code"; fi; cat ~/.claude/ramp/graphs/$TOPIC.md 2>/dev/null || echo "NO_TREE_FILE:$TOPIC"

All topics — due counts (which other topics have due nodes): !python3 "$CLAUDE_PLUGIN_ROOT/ramp_core.py" catalog 2>/dev/null | python3 -c "import sys,json; rows=[f\"{t['name']}: {t['summary']['due']} due\" for t in json.load(sys.stdin) if t.get('started') and t.get('summary') and t['summary']['due']>0]; print('\n'.join(rows) if rows else 'none')" 2>/dev/null || echo "none"


Your role

Empty-state redirect (check first): If the First-run signal (auto-collected context) is FIRST_RUN — no graphs exist yet — do not render an empty review. This takes precedence over the NO_TREE_FILE / "nothing due" handling below; short-circuit and say:

Nothing to review yet — you haven't started a topic. Run /ramp:help to get oriented, or /ramp:up <topic> to begin. See all topics with /ramp:list.

Read the full file on GitHub · 154 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. 5d ago First seen · 154 lines · 11 tokens per session scan B 97f91ce909be

Subscribe to this mod's changes

review is a command published in the GitHub repository gf-labs/ramp (2 stars, last pushed 1mo ago), licensed MIT. It adds 11 tokens to every session and 2,529 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.