Ecommerce.Amazon Product Research Api logo

Ecommerce.Amazon Product Research Api

Organization
nexscope-ai
ecommerce.amazon-product-research-api

Route Amazon product-selection work across market, keyword, competitor, trend, review, and profitability capabilities. Use this skill when the user asks for this exact ecommerce workflow, analysis, data lookup, or deliverable.

Overview

Publishernexscope-ai
Repositorynexscope-ecommerce-skills
Skill nameecommerce.amazon-product-research-api
Stars
104
Forks
14
Bundled files
75
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 75 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by nexscope-ai on GitHub. Read the source before you install it.

Installation

Install the Ecommerce.Amazon Product Research Api AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nexscope-ai/nexscope-ecommerce-skills/tree/main/ecommerce-amazon-product-research-api
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nexscope-ai/nexscope-ecommerce-skills.git /tmp/nexscope-ecommerce-skills
mkdir -p .claude/skills
cp -r /tmp/nexscope-ecommerce-skills/ecommerce-amazon-product-research-api .claude/skills/ecommerce.amazon-product-research-api
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ecommerce.Amazon Product Research Api in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ecommerce.Amazon Product Research Api on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ecommerce.Amazon Product Research Api is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Amazon Product Research Api

Core Concepts

Route Amazon product-selection work across market, keyword, competitor, trend, review, and profitability capabilities.

Core workflow

  1. Identify the marketplace, entity identifiers, date range, filters, and requested output.
  2. Ask only for missing inputs that materially change the result.
  3. Read references/api.json and select the exact package-local script for the required connector, calculation, transformation, or account workflow.
  4. Execute the cataloged mode exactly: run gateway-script and local-script operations with the package-local script recorded in upstreamPath, and follow this document for agent-guided operations.
  5. Validate returned fields and preserve the distinction between source facts, calculations, and recommendations.
  6. Save large results through the runtime and present a concise user-facing summary with the artifact path.

Operation Catalog

OperationModeMutationCallable
aba_querygateway-scriptnoyes
amazon_alexa_searchgateway-scriptnoyes
amazon_opportunity_reportgateway-scriptnoyes
amazon_opportunity_screenergateway-scriptnoyes
amazon_product_detailgateway-scriptnoyes
amazon_reviewsgateway-scriptnoyes
amazon_searchgateway-scriptnoyes
amazon_search_by_imagegateway-scriptnoyes
jiimore_get_niche_infogateway-scriptnoyes
jiimore_get_niche_info_by_keywordgateway-scriptnoyes
jiimore_get_niche_reviewgateway-scriptnoyes
jiimore_page_asins_by_asingateway-scriptnoyes
jiimore_product_discoverygateway-scriptnoyes
junglescout_keyword_by_asingateway-scriptnoyes
junglescout_keyword_by_keywordgateway-scriptnoyes
junglescout_keyword_historygateway-scriptnoyes
junglescout_keyword_sovgateway-scriptnoyes
junglescout_product_databasegateway-scriptnoyes
junglescout_sales_estimatesgateway-scriptnoyes
keepa_product_detailgateway-scriptnoyes
keepa_product_historygateway-scriptnoyes
keepa_product_searchgateway-scriptnoyes
onboardinglocal-scriptnoyes
sellersprite_competitor_lookupgateway-scriptnoyes
sellersprite_market_researchgateway-scriptnoyes
sellersprite_market_statisticsgateway-scriptnoyes
sellersprite_product_searchgateway-scriptnoyes
sellersprite_traffic_keywordgateway-scriptnoyes
sif_asin_keywordsgateway-scriptnoyes
sif_asin_summarygateway-scriptnoyes
sif_keyword_overviewgateway-scriptnoyes
sif_keyword_trafficgateway-scriptnoyes
sorftime_product_detailgateway-scriptnoyes
sorftime_product_searchgateway-scriptnoyes
upload_imagegateway-scriptyesyes

The machine-readable source of truth is references/api.json. Field-level payload rules remain operation-specific; do not invent identifiers, filters, credentials, or marketplace facts.

API Invocation

Every research-tool request must use the full path recorded in references/api.json, beginning with /api/v1/tools/research/. Set NEXSCOPE_PROXY_BASE to the gateway origin only; never call a legacy short path such as /amazon/**, /kalodata/**, or /aigc/** directly.

Run only the package-local script recorded in the selected operation's upstreamPath. Business/tool operations may use the Nexscope proxy; authorization/account operations use their configured Agent/Login service, and third-party connectors use their documented provider endpoint. Never invoke a script from another Skill.

Response handling

For the research HTTP response, require a numeric outer code equal to 0 before using data. Nonzero codes are platform failures; display outer msg without interpreting its wording as a retry instruction. Nexscope preserves upstream messages and translates Chinese to English; successful responses may have msg: null. HTTP 200 alone and nested business code / status do not replace the platform check. See references/api.md for response paths and task-specific states.

Usage Examples

bash
python scripts/aba_query.py --help
# Then run the selected local script with its documented arguments.

python scripts/upload_image.py --confirm --confirm-mutation /path/to/product.png
# Upload through the shared Skill Asset presign -> PUT -> confirm workflow.

For a cataloged mutation, obtain explicit user approval and then pass both --confirm and --confirm-mutation. Never infer confirmation from an earlier read request.

For upload_image, use only POST /api/skill-asset/presign, the returned presigned HTTPS PUT URL, and POST /api/skill-asset/confirm. Treat only the confirm response's publicUrl as the final image URL. Never send NEXSCOPE_API_KEY to the presigned upload host.

Runtime configuration

Business/tool operations require NEXSCOPE_PROXY_BASE plus NEXSCOPE_API_KEY; authorization/account operations require the relevant NEXSCOPE_AGENT_* or NEXSCOPE_LOGIN_* base because those proxy routes are not implemented. Third-party connectors require their documented provider configuration. Install optional libraries named by a script only when that operation is selected. Read references/credentials.md and set only the variables required by the selected script. Never pass secrets in command arguments or persist them in output artifacts.

Use only the hosts, credentials, and endpoints implemented by the package-local script and documented in references/credentials.md. Never substitute an undocumented legacy host or expose secret values.

Display Rules

  • Keep full JSON in the generated nexscope/<date>/<session>/data/ artifact.
  • Show the user the relevant records, assumptions, calculations, and limitations.
  • Redact authorization, tokens, cookies, secrets, and passwords recursively.
  • Do not treat an HTTP 200 response as success when the outer platform code is nonzero; nested business fields are not platform status codes.

Important Limitations

  • Do not fabricate marketplace data or silently fill required business identifiers.
  • Do not retry a mutation after an ambiguous timeout; query status first.
  • Treat legal, compliance, tax, and profitability outputs as decision support, not professional advice.
  • Do not claim real-account, sandbox, ZIP-install, or production validation unless that evidence exists.

References

  • Read references/workflow.md before executing the domain procedure.
  • Read references/api.md for the package contract and examples.
  • Read references/testing.md before claiming a validation level.

Privacy and Errors

Treat marketplace, account, product, advertising, order, supplier, and generated-asset data as private. Keep credentials out of payloads and artifacts. Surface HTTP, application-envelope, upstream-business, malformed-response, and unavailable-connector failures distinctly.

Authentication

Set the NEXSCOPE_API_KEY environment variable. If credentials are missing or expire, visit https://www.nexscope.ai/help/skills-external-access?co-from=skillNS to top up credits.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

and 15 more files.

Frequently asked questions

What does the Ecommerce.Amazon Product Research Api AI skill do?

Route Amazon product-selection work across market, keyword, competitor, trend, review, and profitability capabilities. Use this skill when the user asks for this exact ecommerce workflow, analysis, data lookup, or deliverable.

Why use Ecommerce.Amazon Product Research Api on TypingMind?

Because you install it once and use it with any model. Ecommerce.Amazon Product Research Api is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ecommerce.Amazon Product Research Api in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nexscope-ai/nexscope-ecommerce-skills/tree/main/ecommerce-amazon-product-research-api. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ecommerce.Amazon Product Research Api?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ecommerce.Amazon Product Research Api?

As many as you like. As long as a model supports skills, you can use Ecommerce.Amazon Product Research Api with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ecommerce.Amazon Product Research Api AI skill free?

It is published on GitHub by nexscope-ai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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