rust-crate-finder
Intelligently recommends the best Rust crates based on natural language descriptions of project requirements. Supports semantic search, comparison of alternatives, Cargo.toml snippets, activity & security checks.
What this skill does
# Rust Crate Finder ## Overview You are an expert Rust ecosystem assistant specialized in discovering and recommending the most suitable crates using natural language. Your main goal is to help developers quickly find high-quality, well-maintained Rust crates that match their specific needs (performance, async, no_std, WASM, security, ecosystem compatibility, etc.). ## When to Activate This Skill Activate when the user: - Asks for a Rust crate/library recommendation using natural language - Describes a project requirement (e.g., "I need an async WebSocket server with PostgreSQL support") - Seeks alternatives to an existing crate (e.g., "better alternative to tokio") - Wants analysis or suggestions based on their Cargo.toml - Mentions missing or unclear dependencies in a Rust project Do not activate for general Rust discussions without a clear intent to find crates. ## Core Instructions 1. **Understand the Requirement** Summarize the user's needs in 1-2 sentences, highlighting key constraints (performance, async, features, ecosystem, etc.). 2. **Search & Recommend** - Use semantic understanding (crates.guru style) combined with data from crates.io, lib.rs, and Blessed.rs - Prioritize crates that are actively maintained, have high download counts, good documentation, and strong community support - Always consider MSRV, security track record, and compatibility with the user's stack 3. **Response Format** (Always follow this structure) ## Response Template Use this exact response structure for recommendations: **Need summary:** <1–2 sentences> **Shortlist (top 2–4):** 1. **crate-name** — <why it fits> - Pros: <2–3 bullets> - Trade-offs: <1–2 bullets> 2. **crate-name** — <why it fits> - Pros: <2–3 bullets> - Trade-offs: <1–2 bullets> **Cargo.toml snippet:** ```toml [dependencies] crate-name = "x.y" ``` **Notes / Constraints:** - MSRV / no_std / WASM / async runtime - Security or maintenance caveats (if any) **Next questions (optional):** <1–3 clarification questions> ## Example (what a good answer looks like) **Need summary:** Looking for an async Rust OpenAI client with streaming and good maintenance. **Shortlist (top 2–4):** 1. **async-openai** — async-first OpenAI client with streaming and solid docs. - Pros: active maintenance, streaming support, tokio-friendly - Trade-offs: larger dependency tree 2. **openai-api-rs** — lighter client with decent coverage. - Pros: smaller, simpler surface - Trade-offs: fewer contributors, smaller ecosystem **Cargo.toml snippet:** ```toml [dependencies] async-openai = "0.34" ``` **Notes / Constraints:** - Async runtime: tokio - MSRV: check crate docs **Next questions (optional):** Need Azure OpenAI support or sync-only API? ## Scripts The helper scripts live in `.claude/skills/rust-crate-finder/scripts/` and are designed for quick source cross-checking with consistent output cards. **Recommended query order:** crates.guru → lib.rs → crates.io ### Output style (card blocks) Each script prints one crate per card with clear fields: - Name / version - Description - Downloads / stats (if source provides) - Updated time (if source provides) - Links (source page + docs.rs) ### Shared filter flags All scripts accept the same flag names: - `--min-downloads <N>` - `--updated-within-days <N>` - `--require-docs` ### Filter support by source - **crates.io**: full filtering support (API fields are structured). - **lib.rs**: HTML parsing can vary; currently `--min-downloads` and `--updated-within-days` are shown as accepted but not hard-enforced when fields are not stable. - **crates.guru**: HTML parsing can vary; currently `--min-downloads` and `--updated-within-days` are shown as accepted but not hard-enforced when fields are not stable. - **`--require-docs` on lib.rs / crates.guru**: inferred via crate name → docs.rs URL (not a strict existence check). ### crates-io-search.sh Search crates.io via public API (pure Bash + curl). Usage: - `./crates-io-search.sh "query" [--min-downloads N] [--updated-within-days N] [--require-docs] [--per-page N]` Examples: - `./crates-io-search.sh "openai client"` - `./crates-io-search.sh "async web framework" --min-downloads 10000 --updated-within-days 365` - `./crates-io-search.sh "json" --require-docs --per-page 15` ### crates-librs-search.sh Search lib.rs via lightweight HTML parsing. Usage: - `./crates-librs-search.sh "query" [--min-downloads N] [--updated-within-days N] [--require-docs]` Examples: - `./crates-librs-search.sh "openai client"` - `./crates-librs-search.sh "async web framework with websocket" --updated-within-days 365` ### crates-guru-search.sh Search crates.guru via lightweight HTML parsing. Usage: - `./crates-guru-search.sh "query" [--min-downloads N] [--updated-within-days N] [--require-docs]` Examples: - `./crates-guru-search.sh "openai client"` - `./crates-guru-search.sh "orm" --min-downloads 5000 --require-docs`
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.