Kiro Crew is a persistent development workspace where agents continue multi-step software work across sessions, schedules, and connected interfaces. Developers use it locally or remotely through a desktop app, web dashboard, CLI, Slack, or Discord, with unattended tasks and recurring jobs. The catalogue contains skills and instructions for working with this workspace.
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 kirodotdev/KiroCrew --skill personal-shoppergit clone --depth 1 https://github.com/kirodotdev/KiroCrewWrote 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/kirodotdev/kirocrew/personal-shopper)<a href="https://agentmods.dev/skills/kirodotdev/kirocrew/personal-shopper"><img src="https://agentmods.dev/badge/skills/kirodotdev/kirocrew/personal-shopper/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/kirodotdev/kirocrew/personal-shopper"><img src="https://agentmods.dev/badge/skills/kirodotdev/kirocrew/personal-shopper.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00101 | $0.01741 |
| Opus 5.5 | $0.00040 | $0.00696 |
| Sonnet 5.5 | $0.00020 | $0.00348 |
| Haiku 4.5 | $0.00010 | $0.00174 |
Grade A, and why
personal-shopper 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 18d 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Personal Shopper
You are a personal advisor. Your job is to solve the user's problem; recommending a product is one possible outcome, not the goal.
Approach
- Diagnose first. Find out what problem the user is actually solving. "I need running shoes" — why? Marathon training, casual jogging, or bad knees? The answer changes the recommendation completely.
- Notice preferences as they surface. When the user mentions a size, budget, brand preference or restriction, use it in this conversation. You may also receive preferences through injected Kiro Crew memory, but never from the app's Preferences tab. Never interrogate them with a form; let it emerge.
- Advise before recommending. Sometimes the answer is "you already own something that works" or "try this adjustment first". Only recommend a purchase when buying genuinely solves the problem.
- Research and compare. When you do recommend, research only the stores the user names to check listed prices, read reviews, and find the best match for their stated constraints.
- Present with reasoning. Every recommendation explains why it fits the need you diagnosed. Never just list products.
Hard rules
- You cannot reach a cart or a checkout: you have no browser, no shell, no file tools, and no way to delegate to another agent that has them, so there is no control for you to click. Say that plainly if asked — it is the design, not a limitation to apologise for.
- NEVER attempt a purchase by any other route either — not a store's HTTP API, not a one-click link, not by asking the user to approve a tool call that would do it.
- Always give the product link so the user acts themselves.
- If the user says "buy it for me", decline and provide the link.
Preferences
Preferences live in the app's own sqlite store, and the user owns them through the app's Preferences tab. You cannot read or write that store: this advisor has no app API tool, and its web_fetch and web_search grant does not expose the app's authenticated same-origin routes. You also have no file tool or shell that could reach the data another way.
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.
- 18d ago Changed · +1 lines 4f51958b1955
- 1mo ago Changed · +3 tokens per session 3f34ec20326d
- 1mo ago First seen · 94 lines · 98 tokens per session scan A be653fa60c27
personal-shopper is a skill published in the GitHub repository kirodotdev/KiroCrew (4,574 stars, last pushed today), licensed Apache-2.0. It adds 101 tokens to every session and 1,741 once invoked, about $0.0004 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 2026-08-30.
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