laundry-booking

laundry-booking is a skill for Claude Code, Codex from kongaharsha/hermes_stack. It costs 17 tokens per session (385 once invoked), scanned A, original, MIT.

A browser automation skill for arranging laundry or dry-cleaning pickup and drop-off. It uses a locally controlled Chrome session and guides the user through dates, times, authentication, and confirmation.

In plain words
What is it for?
Use it to book laundry or dry-cleaning services, choose pickup and drop-off slots, handle user-entered verification codes, and record the completed booking.
Why use it?
It handles the multi-step booking process while requiring confirmation of the proposed action and selected time windows before checkout.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to book laundry or dry-cleaning services, choose pickup and drop-off slots, handle user-entered verification codes, and record the completed booking.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kongaharsha/hermes_stack/laundry-booking
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.

Any agent
npx skills add kongaharsha/hermes_stack --skill laundry-booking
Clone the repo
git clone --depth 1 https://github.com/kongaharsha/hermes_stack

Made for: Claude Code, Codex.

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 laundry-booking

README.md
[![agentmods](https://agentmods.dev/badge/skills/kongaharsha/hermes_stack/laundry-booking.svg)](https://agentmods.dev/skills/kongaharsha/hermes_stack/laundry-booking)
Your own site
<a href="https://agentmods.dev/skills/kongaharsha/hermes_stack/laundry-booking"><img src="https://agentmods.dev/badge/skills/kongaharsha/hermes_stack/laundry-booking.svg" alt="Measured on agentmods" height="20"></a>
Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 385 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00017 $0.00385
Opus 5 $0.00009 $0.00192
Sonnet 5 $0.00003 $0.00077
Haiku 4.5 $0.00002 $0.00038

Measured 8d ago against content hash 0f1aa07ee648, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

laundry-booking 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 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.

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.

skills/laundry-booking/SKILL.md · 33 lines

What it actually says

Laundry Booking

Books a laundry or dry-cleaning pickup using a locally-controlled Chrome instance.

Workflow

  1. Confirm Intent: Before triggering any automation, state the proposed action (including proposed pickup/drop-off dates) and confirm with the user.
  2. Setup Browser: Always use headed Chrome (connect to port 9222/headed mode) until requested otherwise (currently planned for the next 4 sessions).
  3. Data Verification: Read ~/brain/concepts/service-preferences.md.
  4. Calendar/Scheduling:
    • First, ask the user if they want the fastest available slots for both pickup and drop-off, or if they want to review all available options.
    • For all dates and times, always confirm the selected windows with the user before final checkout.
  5. Flow Execution:
    • Navigate to provider site.
    • Phone auth/2FA as required (user intervention required for codes).
    • Wizard steps: Select Pickup Date (check for accordions) -> Time -> Drop-off Date -> Time -> Confirm.
    • Always use snapshot -i after navigation to refresh UI state/refs.
  6. Task Completion: Finalize order and log details in ~/brain/logs/services.md.

Implementation Insights (Riverside Laundromat)

  • UI: Multi-step wizard.
  • Pitfalls: Persistent sign-in loops (if activation code fails, refresh/re-navigate), stale elements (refresh refs constantly), multi-page transitions (Confirm button does not auto-finish).
  • If automated interaction stalls, stop and prompt for manual intervention.

Resilience Patterns

  • If automated interaction fails or times out, do NOT retry indefinitely. Stop and inform the user.
  • Prefer explicit confirmation for pickup/drop-off windows.
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. 8d ago First seen · 33 lines · 17 tokens per session scan A 0f1aa07ee648

Subscribe to this mod's changes

laundry-booking is a skill published in the GitHub repository kongaharsha/hermes_stack (5 stars, last pushed 4mo ago), licensed MIT. It adds 17 tokens to every session and 385 once invoked, about $0.0001 per session on Opus 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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