Which Llm
Deterministic decision-ranking API with HTTP 402 USDC payments and outcome credits (discounts).
- Rating
- 4.3 (190 reviews)
- Downloads
- 26,265 downloads
- Version
- 1.0.0
Overview
Deterministic decision-ranking API with HTTP 402 USDC payments and outcome credits (discounts).
Complete Documentation
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Which‑LLM: Outcome‑Driven Decision Optimizer
Overview
Use this skill when you need a deterministic recommendation for which LLM to use under explicit constraints such as cost and quality.
This skill is for calling the Which‑LLM API. It does not run an LLM itself. For paid requests, the AI bot needs access to a crypto wallet.
When to use it
- Pick the cheapest model that still meets a quality target
- Choose a fallback model if the preferred one fails
- Keep model selection deterministic and auditable
- Report execution results and earn credits for later requests
Quick Reference
- API base URL:
https://api.which-llm.com - Primary paid endpoint:
POST /decision/optimize - Outcome endpoint:
POST /decision/outcome - Free discovery endpoints:
GET /capabilities,GET /pricing,GET /status - Payment asset:
USDC - Supported chains: Base, Ethereum, Arbitrum, Optimism, Avalanche
Registry Summary Expectations
Primary credential:WALLET_CREDENTIALSInstall mechanism: instruction-onlyWrites to disk on install:falseDownloads code on install:false
Prerequisites
Before using this skill, have the following ready:
- Ability to make HTTPS requests to
https://api.which-llm.com - Ability to send and receive JSON
- AI bot access to a crypto wallet for paid requests
What this skill does
- Sends requests to the Which‑LLM API
- Uses
POST /decision/optimizeto get a recommended model and fallback plan - Uses
POST /decision/outcometo report real execution results - Explains the request and response shapes for the public API
- Describes how to retry requests after payment has been satisfied externally
What this skill does not do
- It does not call an LLM directly
- It does not execute arbitrary code from your prompt
- It does not require unrelated files or system access beyond API usage and payment handling
Runtime Scope
always_on: false: the skill is not force-installed and does not run continuouslydisable_model_invocation: false: an agent may invoke it on demand- The skill is limited to outbound HTTP API usage and response handling
- For paid requests, the AI bot needs access to a crypto wallet
Payment Model
Paid calls may use HTTP 402 Payment Required.
High-level flow:
- Call
POST /decision/optimize - If the API returns
402, inspect fields such asrequired_amount,accepts, andpayment_reference - Satisfy the payment requirement outside this skill using host- or client-managed infrastructure
- Retry the same request with payment proof headers if available
Endpoints
GET /capabilities
Use this to discover supported constraints, decision types, and payment behavior.
GET /pricing
Use this to check current pricing and supported chains before making a paid request.
GET /status
Use this for service-health checks.
POST /decision/optimize
This is the main endpoint. Send the goal and constraints, then receive:
recommended_modelfallback_plan- decision metadata and explainability fields
{
"goal": "Summarize customer feedback emails into a 5-bullet executive summary",
"constraints": {
"min_quality_score": 0.8,
"max_cost_usd": 0.01
},
"workload": {
"input_tokens": 1200,
"output_tokens": 300,
"requests": 1
},
"task_type": "summarize"
}
If payment is required, the API may first return 402 with fields such as:
required_amountcurrencyaccepts[].chainaccepts[].pay_topayment_reference
X-Payment-ChainX-Payment-TxX-PayerX-Payment-AmountX-Payment-Asset
X-Credit-Token
POST /decision/outcome
Use this after running the recommended model. Report what actually happened so the system can issue a credit token for future use.
Typical request shape:
{
"decision_id": "d4e5f6a7-b8c9-0d1e-2f3a-4b5c6d7e8f90",
"option_used": "openai/gpt-4o-mini",
"actual_cost": 0.008,
"actual_latency": 650,
"quality_score": 0.86,
"success": true
}
Typical response includes:
statusdecision_idoutcome_hashrefund_credit.credit_token
Request Strategy For Agents
- Call
GET /capabilitiesorGET /pricingfirst if you need to discover current payment behavior - Use
POST /decision/optimizeonly when you actually need model selection help - Reuse the returned decision data rather than repeatedly asking the same question
- After running the chosen model, call
POST /decision/outcometo earn credits - Use the host or client payment flow when a paid request requires wallet-backed settlement
Troubleshooting
PAYMENT_REQUIRED
The endpoint needs payment first. Read the 402 response, satisfy the payment requirement externally, then retry with payment proof headers if available.
PAYMENT_INVALID
Check:
- exact amount sent
- correct chain
- correct recipient
- confirmed transaction
- headers match the actual transaction
NO_FEASIBLE_OPTIONS
Your cost and quality constraints are too strict for the available models. Relax the budget or quality threshold and retry.
RATE_LIMIT_EXCEEDED
Back off and retry later. Use an idempotency key for safe retries.
Installation
openclaw install which-llm
💻Code Examples
}
If payment is required, the API may first return `402` with fields such as:
- `required_amount`
- `currency`
- `accepts[].chain`
- `accepts[].pay_to`
- `payment_reference`
Retry the request after external payment handling with:
- `X-Payment-Chain`
- `X-Payment-Tx`
- `X-Payer`
- `X-Payment-Amount`
- `X-Payment-Asset`
If you have a valid credit token, also send:
- `X-Credit-Token`
### `POST /decision/outcome`
Use this after running the recommended model. Report what actually happened so the system can issue a credit token for future use.
Typical request shape:{
"goal": "Summarize customer feedback emails into a 5-bullet executive summary",
"constraints": {
"min_quality_score": 0.8,
"max_cost_usd": 0.01
},
"workload": {
"input_tokens": 1200,
"output_tokens": 300,
"requests": 1
},
"task_type": "summarize"
}{
"decision_id": "d4e5f6a7-b8c9-0d1e-2f3a-4b5c6d7e8f90",
"option_used": "openai/gpt-4o-mini",
"actual_cost": 0.008,
"actual_latency": 650,
"quality_score": 0.86,
"success": true
}Tags
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