alchemy-openapi-skill
Operate Alchemy Prices API reads through UXC with a curated OpenAPI schema, path-templated API-key auth, and read-first guardrails.
What this skill does
# Alchemy Prices API Skill
Use this skill to run Alchemy Prices API operations through `uxc` + OpenAPI.
Reuse the `uxc` skill for shared execution, auth, and error-handling guidance.
## Prerequisites
- `uxc` is installed and available in `PATH`.
- Network access to `https://api.g.alchemy.com`.
- Access to the curated OpenAPI schema URL:
- `https://raw.githubusercontent.com/holon-run/uxc/main/skills/alchemy-openapi-skill/references/alchemy-prices.openapi.json`
- An Alchemy API key.
## Scope
This v1 skill intentionally covers the narrow Prices API surface:
- token price lookup by symbol
- token price lookup by contract address
- historical token prices
This skill does **not** cover:
- node JSON-RPC
- NFT or portfolio APIs
- write operations
- the broader Alchemy API surface
- multi-symbol batch lookup in one `uxc` call
## Authentication
Alchemy Prices API places the API key in the request path: `/prices/v1/{apiKey}/...`.
Configure one API-key credential with a request path prefix template:
```bash
uxc auth credential set alchemy-prices \
--auth-type api_key \
--secret-env ALCHEMY_API_KEY \
--path-prefix-template "/prices/v1/{{secret}}"
uxc auth binding add \
--id alchemy-prices \
--host api.g.alchemy.com \
--scheme https \
--credential alchemy-prices \
--priority 100
```
Validate the active mapping when auth looks wrong:
```bash
uxc auth binding match https://api.g.alchemy.com
```
## Core Workflow
1. Use the fixed link command by default:
- `command -v alchemy-openapi-cli`
- If missing, create it:
`uxc link alchemy-openapi-cli https://api.g.alchemy.com --schema-url https://raw.githubusercontent.com/holon-run/uxc/main/skills/alchemy-openapi-skill/references/alchemy-prices.openapi.json`
- `alchemy-openapi-cli -h`
2. Inspect operation schema first:
- `alchemy-openapi-cli get:/tokens/by-symbol -h`
- `alchemy-openapi-cli post:/tokens/by-address -h`
- `alchemy-openapi-cli post:/tokens/historical -h`
3. Start with narrow single-asset reads before batch historical requests:
- `alchemy-openapi-cli get:/tokens/by-symbol symbols=ETH currency=USD`
- `alchemy-openapi-cli post:/tokens/by-address '{"addresses":[{"network":"eth-mainnet","address":"0xa0b86991c6218b36c1d19d4a2e9eb0ce3606eb48"}],"currency":"USD"}'`
4. Use positional JSON only for the POST endpoints:
- `alchemy-openapi-cli post:/tokens/historical '{"symbol":"ETH","startTime":"2025-01-01T00:00:00Z","endTime":"2025-01-07T00:00:00Z","interval":"1d","currency":"USD"}'`
## Operations
- `get:/tokens/by-symbol`
- `post:/tokens/by-address`
- `post:/tokens/historical`
## Guardrails
- Keep automation on the JSON output envelope; do not use `--text`.
- Parse stable fields first: `ok`, `kind`, `protocol`, `data`, `error`.
- Treat this v1 skill as read-only and prices-only. Do not imply RPC, trade execution, or wallet mutation support.
- API keys are sensitive because they appear in the request path. Use `--secret-env` or `--secret-op`, not shell history literals, when possible.
- `/tokens/by-symbol` is query-based in the live API.
- The live API supports repeated `symbols=` parameters, but this v1 skill intentionally narrows that endpoint to a single `symbols=<TOKEN>` query because current `uxc` query argument handling does not reliably execute array-shaped query parameters.
- Historical requests can expand quickly. Keep time windows tight unless the user explicitly wants a larger backfill.
- `alchemy-openapi-cli <operation> ...` is equivalent to `uxc https://api.g.alchemy.com --schema-url <alchemy_openapi_schema> <operation> ...`.
## References
- Usage patterns: `references/usage-patterns.md`
- Curated OpenAPI schema: `references/alchemy-prices.openapi.json`
- Alchemy Prices API docs: https://www.alchemy.com/docs/reference/prices-api
- Prices API endpoints: https://www.alchemy.com/docs/reference/prices-api-endpoints
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.