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 finsilabs/awesome-ecommerce-skills --skill search-autocompletegit clone --depth 1 https://github.com/finsilabs/awesome-ecommerce-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/finsilabs/awesome-ecommerce-skills/search-autocomplete)<a href="https://agentmods.dev/skills/finsilabs/awesome-ecommerce-skills/search-autocomplete"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/search-autocomplete/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/finsilabs/awesome-ecommerce-skills/search-autocomplete"><img src="https://agentmods.dev/badge/skills/finsilabs/awesome-ecommerce-skills/search-autocomplete.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 | $0.00027 | $0.02888 |
| Opus 5 | $0.00014 | $0.01444 |
| Sonnet 5 | $0.00005 | $0.00578 |
| Haiku 4.5 | $0.00003 | $0.00289 |
Grade A, and why
search-autocomplete 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 9d 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Search Autocomplete
Overview
Implement a typeahead search experience that surfaces product suggestions, categories, and content as shoppers type. Combines client-side debouncing with server-side fuzzy matching, applies merchandising rules (boosts, pins, synonyms), and renders a structured dropdown that drives measurable conversion lift.
When to Use This Skill
- When shoppers are failing to find products through browse navigation alone
- When site search click-through rates are below 30% of searches
- When adding a search-as-you-type experience to an existing search endpoint
- When integrating a third-party search service (Algolia, Elasticsearch, Typesense)
- When implementing merchandising rules to boost promoted products in results
- When supporting multi-language storefronts requiring synonym and phonetic matching
Core Instructions
Step 1: Determine the merchant's platform and choose the right approach
| Platform | Recommended Approach | Why |
|---|---|---|
| Shopify | Install Search & Discovery app (free, by Shopify) for synonym/boost configuration + Searchie or Boost Commerce app for full autocomplete dropdown | Search & Discovery improves the built-in Shopify search with synonyms and product boosts; Boost Commerce ($19/mo) adds a fully styled autocomplete dropdown with category results and merchandising rules |
| WooCommerce | Install FiboSearch – AJAX Search for WooCommerce (free/paid) or SearchWP + SearchWP Live Search extension | FiboSearch adds an instant AJAX autocomplete dropdown to the WooCommerce search bar with product images, prices, and category results — no custom code needed |
| BigCommerce | Enable Search Suggestions in Storefront → Search settings + install Klevu Smart Search or Searchspring for advanced autocomplete | BigCommerce's native search has basic autocomplete; Klevu ($449+/mo) and Searchspring add AI-powered autocomplete, synonym management, and merchandising rules |
| Custom / Headless | Build with Algolia InstantSearch.js (recommended) or self-hosted Typesense; implement debounced input, AbortController for race conditions, and ARIA combobox pattern | Algolia offers the best developer experience with a generous free tier (10K searches/month); Typesense is the self-hosted alternative |
What ships with it
7 files 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.
- evals/algolia-index-configuration-and-merchand/criteria.json 2.1 KB
- evals/algolia-index-configuration-and-merchand/task.md 1.6 KB
- evals/backend-autocomplete-endpoint/criteria.json 2.4 KB
- evals/backend-autocomplete-endpoint/task.md 1.4 KB
- evals/frontend-autocomplete-component/criteria.json 2.7 KB
- evals/frontend-autocomplete-component/task.md 1.8 KB
- tile.json 240 B
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.
- 9d ago First seen · 241 lines · 27 tokens per session scan A df9be3d62dbb
search-autocomplete is a skill published in the GitHub repository finsilabs/awesome-ecommerce-skills (52 stars, last pushed 6mo ago), licensed MIT. It adds 27 tokens to every session and 2,888 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 2026-09-03.
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algolia-data-modeling
Algolia data modeling and indexing guidance. Use before or alongside indexing records or building Algolia search UI for net-new search, browse, autocomplete, ecommerce, personalization, Dynamic Re-Ranking, recommendations, or analytics-aware implementations. Makes record shape, objectID, display fields, facets…
algolia-autocomplete
Build and review Algolia Autocomplete and query suggestion experiences. Use when planning or implementing typeahead, query suggestions, recent searches, popular searches, federated autocomplete panels, product/content suggestions, detached mobile mode, plugins, keyboard navigation, insights events, or Autocomplete…