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cpbox-llm-context

USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity...

MIT-0 · Free to use, modify, and redistribute. No attribution required.
2 · 13 · 0 current installs · 0 all-time installs
byspringmint@sprintmint
MIT-0
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Purpose & Capability
Name/description align with the instructions: the SKILL.md documents a REST API that returns pre-extracted web content for RAG/LLM grounding and uses cpbox.io/cppay.finance for delivery and payment.
!
Instruction Scope
The runtime instructions instruct the agent to call external endpoints (cpbox.io and cppay.finance) and to include optional location headers (X-Loc-Lat, X-Loc-Long, etc.). Passing location headers can leak sensitive location data. The doc also references an external README path and a payment signing flow (EIP-712) that requires producing a PAYMENT-SIGNATURE header — these runtime steps can involve private keys or wallet interactions that are not declared. The skill does not tell the agent how to obtain or protect those secrets, which is a scope and privacy concern.
!
Install Mechanism
Although the skill has no formal install spec or code files, the SKILL.md recommends using `npx @springmint/x402-payment` to automatically handle payment. Running `npx` will fetch and execute code from the npm registry at runtime — this is equivalent to running third-party code and can have side effects. That runtime dependency is not captured in the registry metadata and elevates risk.
Credentials
The skill declares no required env vars or credentials, which matches the metadata. However, the payment flow (EIP-712 signing) implies the client must generate a PAYMENT-SIGNATURE (wallet/private-key usage). If automated, an SDK or agent may need access to signing keys or wallet integrations. Also, the optional location headers can expose sensitive personal data; these are not explicitly called out as sensitive in the metadata.
Persistence & Privilege
The skill does not request persistent/system-level privileges; always is false and there are no config paths or declared changes to other skills. Autonomous invocation remains possible (the platform default) but is not combined with other high privileges.
What to consider before installing
This skill appears to do what it says (provide LLM-ready web content) but pay attention to two runtime risks before installing or using it: (1) The SKILL.md recommends running `npx @springmint/x402-payment` to handle payments — that will fetch and execute third-party code at runtime. Only run this if you trust the package and have reviewed it, or run it in an isolated environment. (2) The API supports optional location headers and requires an EIP-712 PAYMENT-SIGNATURE for settlement. Avoid providing private keys or persistent wallet secrets to automation; prefer interactive wallet signing or ephemeral keys. Don’t enable or forward location headers unless you intend to share location with cpbox.io. If you need higher confidence, ask the publisher for: a) the payment SDK source or npm package name and a link to its repo and audit, b) clarification of how signing is expected to be performed (interactive wallet vs. env-provided key), and c) a privacy policy / data retention statement from cpbox.io and cppay.finance. If you cannot obtain that information, treat the runtime `npx` step and any automatic signing as a potential security/privacy risk and sandbox it.

Like a lobster shell, security has layers — review code before you run it.

Current versionv1.0.0
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License

MIT-0
Free to use, modify, and redistribute. No attribution required.

SKILL.md

LLM Context

Paid LLM Context proxy via x402 pay-per-use (HTTP 402).

Prerequisites: This skill requires x402-payment. Complete the setup steps before first use.

Service URLs

RoleDomain
API Providerhttps://www.cpbox.io
Facilitatorhttps://www.cppay.finance

Endpoint (Agent Interface)

GET  /api/x402/llm-context
POST /api/x402/llm-context/post

Payment Flow (x402 Protocol)

  1. First request (no PAYMENT-SIGNATURE) -> 402 Payment Required with requirements JSON
  2. Client signs (EIP-712) -> PAYMENT-SIGNATURE
  3. Retry with PAYMENT-SIGNATURE -> Server settles and returns JSON

With @springmint/x402-payment or x402-sdk-go, payment is automatic.

LLM Context delivers pre-extracted, relevance-ranked web content optimized for grounding LLM responses in real-time search results. Unlike traditional web search APIs that return links and snippets, LLM Context extracts the actual page content—text chunks, tables, code blocks, and structured data—so your LLM or AI agent can reason over it directly.

LLM Context vs AI Grounding

FeatureLLM Context (this)AI Grounding (answers)
OutputRaw extracted content for YOUR LLMEnd-to-end AI answers with citations
InterfaceREST API (GET/POST)OpenAI-compatible /chat/completions
SearchesSingle search per requestMulti-search (iterative research)
SpeedFast (<1s)Slower
PlanSearchAnswers
Endpoint/res/v1/llm/context/res/v1/chat/completions
Best forAI agents, RAG pipelines, tool callsChat interfaces, research mode

Endpoint

GET  https://www.cpbox.io/api/x402/llm-context
POST https://www.cpbox.io/api/x402/llm-context/post

Authentication: handled by x402 payment middleware

Optional Headers:

  • Accept-Encoding: gzip — Enable gzip compression

Quick Start

GET Request

curl -s "https://www.cpbox.io/api/x402/llm-context?q=tallest+mountains+in+the+world" \
  -H "Accept: application/json"

POST Request (JSON body)

curl -s --compressed -X POST "https://www.cpbox.io/api/x402/llm-context/post" \
  -H "Accept: application/json" \
  -H "Accept-Encoding: gzip" \
  -H "Content-Type: application/json" \
  -d '{"q": "tallest mountains in the world"}'

With Goggles (Inline)

curl -s "https://www.cpbox.io/api/x402/llm-context" \
  -H "Accept: application/json" \
  -G \
  --data-urlencode "q=rust programming" \
  --data-urlencode 'goggles=$discard
$site=docs.rs
$site=rust-lang.org'

Using with x402-payment

npx @springmint/x402-payment \
  --url "https://www.cpbox.io/api/x402/llm-context?q=rust+ownership&maximum_number_of_tokens=4096" \
  --method GET

Parameters

Query Parameters

ParameterTypeRequiredDefaultDescription
qstringYes-Search query (1-400 chars, max 50 words)
countrystringNoUSSearch country (2-letter country code or ALL)
search_langstringNoenLanguage preference (2+ char language code)
countintNo20Max search results to consider (1-50)

Context Size Parameters

ParameterTypeRequiredDefaultDescription
maximum_number_of_urlsintNo20Max URLs in response (1-50)
maximum_number_of_tokensintNo8192Approximate max tokens in context (1024-32768)
maximum_number_of_snippetsintNo50Max snippets across all URLs (1-100)
maximum_number_of_tokens_per_urlintNo4096Max tokens per individual URL (512-8192)
maximum_number_of_snippets_per_urlintNo50Max snippets per individual URL (1-100)

Filtering & Local Parameters

ParameterTypeRequiredDefaultDescription
context_threshold_modestringNobalancedRelevance threshold for including content (strict/balanced/lenient)
enable_localboolNonullLocal recall control (true/false/null, see below)
gogglesstring/listNonullGoggle URL or inline definition for custom re-ranking

Context Size Guidelines

Task Typecountmax_tokensExample
Simple factual52048"What year was Python created?"
Standard queries208192"Best practices for React hooks"
Complex research5016384"Compare AI frameworks for production"

Larger context windows provide more information but increase latency and cost (of your inference). Start with defaults and adjust.

Threshold Modes

ModeBehavior
strictHigher threshold — fewer but more relevant results
balancedDefault — good balance between coverage and relevance
lenientLower threshold — more results, may include less relevant content

Local Recall

The enable_local parameter controls location-aware recall:

ValueBehavior
null (not set)Auto-detect — local recall enabled when any location header is provided
trueForce local — always use local recall, even without location headers
falseForce standard — always use standard web ranking, even with location headers

For most use cases, omit enable_local and let the API auto-detect from location headers.

Location Headers

HeaderTypeDescription
X-Loc-LatfloatLatitude (-90.0 to 90.0)
X-Loc-LongfloatLongitude (-180.0 to 180.0)
X-Loc-CitystringCity name
X-Loc-StatestringState/region code (ISO 3166-2)
X-Loc-State-NamestringState/region name
X-Loc-Countrystring2-letter country code
X-Loc-Postal-CodestringPostal code

Priority: X-Loc-Lat + X-Loc-Long take precedence. When provided, text-based headers (City, State, Country, Postal-Code) are not used for location resolution. Provide text-based headers only when you don't have coordinates.

Example: With Coordinates

curl -s "https://www.cpbox.io/api/x402/llm-context" \
  -H "Accept: application/json" \
  -H "X-Loc-Lat: 37.7749" \
  -H "X-Loc-Long: -122.4194" \
  -G \
  --data-urlencode "q=best coffee shops near me"

Example: With Place Name

curl -s "https://www.cpbox.io/api/x402/llm-context" \
  -H "Accept: application/json" \
  -H "X-Loc-City: San Francisco" \
  -H "X-Loc-State: CA" \
  -H "X-Loc-Country: US" \
  -G \
  --data-urlencode "q=best coffee shops near me"

Goggles (Custom Ranking)

Goggles let you control which sources ground your LLM — essential for RAG quality.

Use CaseGoggle Rules
Official docs only$discard\n$site=docs.python.org
Exclude user content$discard,site=reddit.com\n$discard,site=stackoverflow.com
Academic sources$discard\n$site=arxiv.org\n$site=.edu
No paywalls$discard,site=medium.com
MethodExample
Hosted--data-urlencode "goggles=https://<hosted-goggle-url>"
Inline--data-urlencode 'goggles=$discard\n$site=example.com'

Hosted goggles should be hosted on a public URL and include ! name:, ! description:, ! author: headers. Inline rules need no registration.

Syntax: $boost=N / $downrank=N (1–10), $discard, $site=example.com. Combine with commas: $site=example.com,boost=3. Separate rules with \n (%0A).

Allow list: $discard\n$site=docs.python.org\n$site=developer.mozilla.orgBlock list: $discard,site=pinterest.com\n$discard,site=quora.com

Resources: See your upstream provider's Goggles documentation.

Response Format

Standard Response

{
  "grounding": {
    "generic": [
      {
        "url": "https://example.com/page",
        "title": "Page Title",
        "snippets": [
          "Relevant text chunk extracted from the page...",
          "Another relevant passage from the same page..."
        ]
      }
    ],
    "map": []
  },
  "sources": {
    "https://example.com/page": {
      "title": "Page Title",
      "hostname": "example.com",
      "age": ["Wednesday, January 15, 2025", "2025-01-15", "392 days ago"]
    }
  }
}

Local Response (with enable_local)

{
  "grounding": {
    "generic": [...],
    "poi": {
      "name": "Business Name",
      "url": "https://business.com",
      "title": "Title of business.com website",
      "snippets": ["Business details and information..."]
    },
    "map": [
      {
        "name": "Place Name",
        "url": "https://place.com",
        "title": "Title of place.com website",
        "snippets": ["Place information and details..."]
      }
    ]
  },
  "sources": {
    "https://business.com": {
      "title": "Business Name",
      "hostname": "business.com",
      "age": null
    }
  }
}

Response Fields

FieldTypeDescription
groundingobjectContainer for all grounding content by type
grounding.genericarrayArray of URL objects with extracted content (main grounding data)
grounding.generic[].urlstringSource URL
grounding.generic[].titlestringPage title
grounding.generic[].snippetsarrayExtracted smart chunks relevant to the query
grounding.poiobject/nullPoint of interest data (only with local recall)
grounding.poi.namestring/nullPoint of interest name
grounding.poi.urlstring/nullPOI source URL
grounding.poi.titlestring/nullPOI page title
grounding.poi.snippetsarray/nullPOI text snippets
grounding.maparrayMap/place results (only with local recall)
grounding.map[].namestring/nullPlace name
grounding.map[].urlstring/nullPlace source URL
grounding.map[].titlestring/nullPlace page title
grounding.map[].snippetsarray/nullPlace text snippets
sourcesobjectMetadata for all referenced URLs, keyed by URL
sources[url].titlestringPage title
sources[url].hostnamestringSource hostname
sources[url].agearray/nullPage modification dates (when available)

Note: Snippets may contain plain text OR JSON-serialized structured data (tables, schemas, code blocks). LLMs handle this mixed format well.

Use Cases

  • AI Agents: Give your agent a web search tool that returns ready-to-use content in a single call
  • RAG Pipelines: Ground LLM responses in fresh, relevant web content
  • AI Assistants & Chatbots: Provide factual answers backed by real sources
  • Question Answering: Retrieve focused context for specific queries
  • Fact Checking: Verify claims against current web content
  • Content Research: Gather source material on any topic with one API call

Best Practices

  • Token budget: Start with defaults (maximum_number_of_tokens=8192, count=20). Reduce for simple lookups, increase for complex research.
  • Source quality: Use Goggles to restrict to trusted sources. Set context_threshold_mode=strict when precision > recall.
  • Performance: Use smallest count and maximum_number_of_tokens that meet your needs. For local queries, provide location headers.

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