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.
npx skills add larya-dot-eu/undrift --skill undrift-fullgit clone --depth 1 https://github.com/larya-dot-eu/undriftWrote 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/skills/larya-dot-eu/undrift/undrift-full)<a href="https://agentmods.dev/skills/larya-dot-eu/undrift/undrift-full"><img src="https://agentmods.dev/badge/skills/larya-dot-eu/undrift/undrift-full/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/skills/larya-dot-eu/undrift/undrift-full"><img src="https://agentmods.dev/badge/skills/larya-dot-eu/undrift/undrift-full.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 | $0.00066 | $0.02835 |
| Opus 5.5 | $0.00026 | $0.01134 |
| Sonnet 5.5 | $0.00013 | $0.00567 |
| Haiku 4.5 | $0.00007 | $0.00283 |
Grade A, and why
undrift-full 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 1mo 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 — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Undrift Full — Session Pattern Mining → CLAUDE.md Rules
You are acting as a meta-learning agent for this project, running entirely in the main agent — no subagents. Your mission is to scan past sessions, extract recurring corrections, and distil them into durable CLAUDE.md rules — so the same mistakes never have to be corrected twice.
Step 0 — Locate & Scope Sessions
- Run
pwdto identify the current project directory - If
$ARGUMENTSis provided, treat it as a path override for the target project - Validate the path: resolve it to an absolute path and confirm it exists
inside
~/.claude/projects/. If it does not match any known project directory, stop immediately and tell the user — do not proceed. - Locate the matching session directory under
~/.claude/projects/ - List all available sessions, sorted by modification date (newest first)
- Cap scope at the last 50 sessions. If fewer than 10 exist, proceed and note the limited sample size.
- Report: "Found N sessions for [project]. Analysing the most recent 50."
Step 1 — Filter + Extract
Run the following bash loop in the main agent. It processes sessions newest-first, skips sessions with fewer than 3 text-based user turns, extracts user text content, and stops when the global 2000-line cap is reached.
Verified JSONL structure: each line in a session file is a JSON object. User
messages have "type": "user" with a nested "message" object whose "content"
is either a plain string or an array of content blocks. Text turns have content
blocks with "type": "text"; tool results have "type": "tool_result" and do
not count as user turns.
lines=0
for f in $(ls -t <session_dir>/*.jsonl 2>/dev/null | head -50); do
# Count text-based user turns only (excludes tool results)
turn_count=$(jq -r 'select(.type == "user") |
.message.content |
if type == "string" then "T"
elif (map(select(.type == "text")) | length) > 0 then "T"
else empty
end' "$f" 2>/dev/null | wc -l | tr -d ' ')
[ "${turn_count:-0}" -lt 3 ] && continue
# Extract user text content
extracted=$(jq -r 'select(.type == "user") |
.message.content |
if type == "string" then .
else (.[]? | select(.type == "text") | .text)
end' "$f" 2>/dev/null)
new_lines=$(echo "$extracted" | wc -l)
if [ $((lines + new_lines)) -gt 2000 ]; then
echo "CAP_HIT:$(basename $f)"
break
fi
echo "=== SESSION: $(basename $f) ==="
echo "$extracted"
lines=$((lines + new_lines))
done
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.
- 1mo ago First seen · 263 lines · 66 tokens per session scan A 2a5b4e942a99
undrift-full is a skill published in the GitHub repository larya-dot-eu/undrift (2 stars, last pushed 4mo ago), licensed MIT. It adds 66 tokens to every session and 2,835 once invoked, about $0.0003 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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