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 woohyun212/security-skill --skill encoding-toolkitgit clone --depth 1 https://github.com/woohyun212/security-skillWrote 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/woohyun212/security-skill/encoding-toolkit)<a href="https://agentmods.dev/skills/woohyun212/security-skill/encoding-toolkit"><img src="https://agentmods.dev/badge/skills/woohyun212/security-skill/encoding-toolkit/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/woohyun212/security-skill/encoding-toolkit"><img src="https://agentmods.dev/badge/skills/woohyun212/security-skill/encoding-toolkit.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 | $0.00035 | $0.01714 |
| Opus 5.5 | $0.00014 | $0.00686 |
| Sonnet 5.5 | $0.00007 | $0.00343 |
| Haiku 4.5 | $0.00003 | $0.00171 |
Grade A, and why
encoding-toolkit scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
import re, base64, urllib.parse, sys How it starts
The opening of the file, as written. The whole thing — 224 lines — stays where its author put it; the contents beside it link to each section on GitHub.
What this skill does
Automatically detects the encoding format of an input string and performs encode/decode conversions across Base64, URL encoding, Hex, HTML entities, ROT13, and JWT formats. Uses only standard tools: base64, python3, and xxd.
When to use
- Analyzing encoded strings found in web requests or responses
- Stripping multiple encoding layers in CTF challenges
- Inspecting JWT token headers and payloads
- Converting payloads into various formats for WAF bypass testing
Prerequisites
python3(uses standard library, no extra installation needed)base64command (built into Linux/macOS)xxdcommand (built into Linux/macOS)
Inputs
| Variable | Description | Example |
|---|---|---|
INPUT |
Input string to convert | SGVsbG8gV29ybGQ= |
MODE |
Operation to perform (see list below) | base64-decode |
Workflow
Step 1: Auto-detect encoding
INPUT="SGVsbG8gV29ybGQ="
echo "=== Auto-detect encoding ==="
python3 - <<PYEOF
import re, base64, urllib.parse, sys
data = """${INPUT}"""
results = []
# Base64 detection
if re.fullmatch(r'[A-Za-z0-9+/]*={0,2}', data) and len(data) % 4 == 0 and len(data) > 0:
try:
decoded = base64.b64decode(data).decode('utf-8', errors='replace')
results.append(f"[Base64 possible] decoded: {decoded[:80]}")
except Exception:
pass
# URL encoding detection
if '%' in data:
try:
decoded = urllib.parse.unquote(data)
results.append(f"[URL encoding possible] decoded: {decoded[:80]}")
except Exception:
pass
# Hex detection
if re.fullmatch(r'[0-9a-fA-F]+', data) and len(data) % 2 == 0:
try:
decoded = bytes.fromhex(data).decode('utf-8', errors='replace')
results.append(f"[Hex possible] decoded: {decoded[:80]}")
except Exception:
pass
# HTML entity detection
if '&' in data and ';' in data:
import html
decoded = html.unescape(data)
results.append(f"[HTML entity possible] decoded: {decoded[:80]}")
# JWT detection
if data.count('.') == 2 and re.match(r'^[A-Za-z0-9_-]+\.[A-Za-z0-9_-]+\.[A-Za-z0-9_-]+$', data):
results.append("[JWT possible] 3-part dot structure detected -> use Step 4 JWT decode")
if results:
for r in results:
print(r)
else:
print("Auto-detection failed -> specify MODE manually for conversion")
PYEOF
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 · 224 lines · 35 tokens per session scan A 9cb93e765511
encoding-toolkit is a skill published in the GitHub repository woohyun212/security-skill (22 stars, last pushed 6mo ago), licensed MIT. It adds 35 tokens to every session and 1,714 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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