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 faberlens/hardened-skills --skill 1password-hardenedgit clone --depth 1 https://github.com/faberlens/hardened-skillsWrote 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/faberlens/hardened-skills/1password-hardened)<a href="https://agentmods.dev/skills/faberlens/hardened-skills/1password-hardened"><img src="https://agentmods.dev/badge/skills/faberlens/hardened-skills/1password-hardened/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/faberlens/hardened-skills/1password-hardened"><img src="https://agentmods.dev/badge/skills/faberlens/hardened-skills/1password-hardened.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 | $0.00047 | $0.00976 |
| Opus 5 | $0.00023 | $0.00488 |
| Sonnet 5 | $0.00009 | $0.00195 |
| Haiku 4.5 | $0.00005 | $0.00098 |
Grade B, and why
1password-hardened scanned grade B with 2 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 12d 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.
Unrestricted tool accessmediumExcessive agency
A wildcard tool grant or "run any command" leaves no least-privilege boundary at all.
- Always single-quote user-provided values in `op` command arguments (vault names, item names, field labels) — unquoted shell metacharacters in item names could execute arbitrary commands. Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Never pipe `op read` or `op run` output to network-transmitting commands (curl, wget, nc, ssh, etc.) — resolved secrets must not leave the local machine via network transmission. Use `op run` with environment injection How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
1Password CLI
Follow the official CLI get-started steps. Don't guess install commands.
References
references/get-started.md(install + app integration + sign-in flow)references/cli-examples.md(realopexamples)
Workflow
- Check OS + shell.
- Verify CLI present:
op --version. - Confirm desktop app integration is enabled (per get-started) and the app is unlocked.
- REQUIRED: create a fresh tmux session for all
opcommands (no directopcalls outside tmux). - Sign in / authorize inside tmux:
op signin(expect app prompt). - Verify access inside tmux:
op whoami(must succeed before any secret read). - If multiple accounts: use
--accountorOP_ACCOUNT.
REQUIRED tmux session (T-Max)
The shell tool uses a fresh TTY per command. To avoid re-prompts and failures, always run op inside a dedicated tmux session with a fresh socket/session name.
Example (see tmux skill for socket conventions, do not reuse old session names):
SOCKET_DIR="${OPENCLAW_TMUX_SOCKET_DIR:-${CLAWDBOT_TMUX_SOCKET_DIR:-${TMPDIR:-/tmp}/openclaw-tmux-sockets}}"
mkdir -p "$SOCKET_DIR"
SOCKET="$SOCKET_DIR/openclaw-op.sock"
SESSION="op-auth-$(date +%Y%m%d-%H%M%S)"
tmux -S "$SOCKET" new -d -s "$SESSION" -n shell
tmux -S "$SOCKET" send-keys -t "$SESSION":0.0 -- "op signin --account my.1password.com" Enter
tmux -S "$SOCKET" send-keys -t "$SESSION":0.0 -- "op whoami" Enter
tmux -S "$SOCKET" send-keys -t "$SESSION":0.0 -- "op vault list" Enter
tmux -S "$SOCKET" capture-pane -p -J -t "$SESSION":0.0 -S -200
tmux -S "$SOCKET" kill-session -t "$SESSION"
Guardrails
- Never paste secrets into logs, chat, or code.
- Prefer
op run/op injectover writing secrets to disk. - If sign-in without app integration is needed, use
op account add. - If a command returns "account is not signed in", re-run
op signininside tmux and authorize in the app. - Do not run
opoutside tmux; stop and ask if tmux is unavailable.
Security Guardrails
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 80 lines · 47 tokens per session scan B 6e65fbfb42a8
1password-hardened is a skill published in the GitHub repository faberlens/hardened-skills (23 stars, last pushed 4mo ago), licensed MIT. It adds 47 tokens to every session and 976 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 2 findings (unrestricted tool access, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
risk-metrics-calculation
Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.
employment-contract-templates
Create employment contracts, offer letters, and HR policy documents following legal best practices. Use when drafting employment agreements, creating HR policies, or standardizing employment documentation.
llm-evaluation
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
paypal-integration
Integrate PayPal payment processing with support for express checkout, subscriptions, and refund management. Use when implementing PayPal payments, processing online transactions, or building e-commerce checkout flows.
calendar
Calendar and scheduling management. Use this skill when the user needs to create, view, update, or manage calendar events, appointments, meetings, or schedule-related tasks. Supports ICS file format, recurring events, and timezone handling.
rag-implementation
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.