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 lemon-etvibe/prompt-vault --skill initgit clone --depth 1 https://github.com/lemon-etvibe/prompt-vaultWrote 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/lemon-etvibe/prompt-vault/init)<a href="https://agentmods.dev/skills/lemon-etvibe/prompt-vault/init"><img src="https://agentmods.dev/badge/skills/lemon-etvibe/prompt-vault/init/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/lemon-etvibe/prompt-vault/init"><img src="https://agentmods.dev/badge/skills/lemon-etvibe/prompt-vault/init.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 | $0.00052 | $0.00861 |
| Opus 5 | $0.00026 | $0.00430 |
| Sonnet 5 | $0.00010 | $0.00172 |
| Haiku 4.5 | $0.00005 | $0.00086 |
Grade C, and why
init scanned grade C with 3 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
curl -s -X POST http://colormind.io/api/ -d '{"model":"default"}' Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
PLUGIN_ROOT=$(find ~/.claude/plugins -name "init.sh" -path "*/prompt-vault/scripts/*" 2>/dev/null | head -1 | sed 's|/scripts/init.sh$||') Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST http://colormind.io/api/ -d '{"model":"default"}' How it starts
The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Set up the prompt-vault logging environment for a project.
This skill collects user preferences, then delegates all file creation to init.sh.
Step 0: Locate the plugin root
Find the init.sh script path:
PLUGIN_ROOT=$(find ~/.claude/plugins -name "init.sh" -path "*/prompt-vault/scripts/*" 2>/dev/null | head -1 | sed 's|/scripts/init.sh$||')
echo "PLUGIN_ROOT=${PLUGIN_ROOT}"
If PLUGIN_ROOT is empty, stop and tell the user the plugin is not installed properly.
Step 1: Language
Check $ARGUMENTS:
en→LANG=en, skip askingko→LANG=ko, skip asking- empty → ask:
Choose language / 언어 선택: [1] English (default) [2] 한국어
Step 2: Model & Context
Ask which model/plan is in use:
| Model | context_tokens | warn_bytes |
|---|---|---|
| Opus 4.6 / Sonnet 4.5 / Haiku 4.5 (200K) | 200000 | 640000 |
| Extended (1M) | 1000000 | 3200000 |
Step 3: Project Metadata
project_name: default = current directory nameproject_description: one-line description (default: empty)
Step 4: Palette
Generate a 5-color palette:
# Primary: colormind.io API (free, no key)
curl -s -X POST http://colormind.io/api/ -d '{"model":"default"}'
# Convert RGB → HEX array
# Fallback: random from curated palettes
jq -r ".[$RANDOM_INDEX]" "${PLUGIN_ROOT}/data/palettes.json"
Step 5: Auto-Logging
Ask:
- en: "Enable auto-logging? (Turn-count based automatic recording via Stop hook)"
- ko: "자동 로깅을 활성화할까요? (Stop 훅에서 턴 수 기반 자동 기록)"
If yes → auto_log=true, turn_threshold=3
If no → auto_log=false
Step 6: Run init.sh
MUST execute this command — this is the core of initialization:
bash "${PLUGIN_ROOT}/scripts/init.sh" \
"$PWD" \
"<LANG>" \
"<MODEL_ID>" \
"<CONTEXT_TOKENS>" \
"<WARN_BYTES>" \
"<PROJECT_NAME>" \
"<PROJECT_DESC>" \
'<PALETTE_JSON>' \
"<AUTO_LOG_ENABLED>" \
"<TURN_THRESHOLD>"
The script creates ALL required files:
.local/logs/directory.local/logs/.config(NOT config.json — the file MUST be named.config).local/logs/_index.md.gitignoreentryCLAUDE.mdlogging protocol section
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.
- 8d ago First seen · 111 lines · 52 tokens per session scan C 777092240357
init is a skill published in the GitHub repository lemon-etvibe/prompt-vault (2 stars, last pushed 5mo ago), licensed MIT. It adds 52 tokens to every session and 861 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 3 findings (sends data to an external url, reads agent configuration directories, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
brainstorm
Interactive idea maturation — explore, research, shape raw ideas into actionable plans. Use when you have a rough idea and want to think it through.
ship
Ship a build — pre-flight checks, deploy, document, verify, monitor. Use when deploying code, publishing packages, or releasing.
sitrep
Situational awareness — where am I, what was I doing, what's next. Context recovery after compression, confusion, or mid-session reorientation.
fastapi
FastAPI best practices + Pydantic. Use when building or reviewing FastAPI APIs.
docs
Generate and update living documentation — tech docs, user guides, philosophy overview. Composable building block for CLOSE and other skills.
memory
Knowledge system ops — recall, pollinate, audit docs. Subcommands: recall, pollinate, review. Use for pattern queries, cross-client transfer, or audits.