youdotcom
Use You.com Search, conditional livecrawl/contents, and narrow Research API follow-ups through the official client first, with direct HTTP only as fallback. - MANDATORY TRIGGERS: You.com, youdotcom, YDC, YDC API, You.com API, livecrawl, contents, research lite, research deep, cited web research, direct API integration - Use when: web-grounded search or extraction is needed, or when a repo script should call You.com programmatically
What this skill does
# You.com Search, Conditional Crawl, and Narrow Research
Use You.com through the official client when possible. In this repo, prefer
`@youdotcom-oss/api` inside Bun scripts and let `varlock` inject
`YDC_API_KEY`.
Use raw `fetch` only when:
- the official client does not support the needed endpoint behavior
- or you are debugging a client-specific issue
## What We Learned
Default behavior in this repo should be:
1. start with **Search**
2. use **livecrawl** or **Contents** only when search snippets are insufficient
3. use **Research** only when the question is narrow enough to anchor well
This matters because:
- broad `research lite` prompts often return weak or no-result output
- raw `fetch` against You.com Search can show transport/decompression instability
under longer batch runs
- the official `@youdotcom-oss/api` client is the better default scripted path
before adding custom retry logic
## Repo Rules
- Prefer repo scripts over shell-heavy one-offs.
- Prefer `@youdotcom-oss/api` over raw `fetch` for Bun scripts.
- Use `varlock` to inject `YDC_API_KEY`.
- Use Search as the default enrichment step in modnet flows.
- Use livecrawl only when the first search still leaves module shape unclear.
- Use Contents only when you already know the URL set.
- Use Research as a constrained follow-up tool, not as the default search
replacement.
## Authentication
In this repo:
```ts
const apiKey = process.env.YDC_API_KEY
if (!apiKey) throw new Error('YDC_API_KEY is required')
```
Typical command surface:
```bash
bunx varlock run -- bun scripts/some-script.ts
```
## Preferred Programmatic Path
Use the official client first:
```ts
import { fetchSearchResults } from '@youdotcom-oss/api'
const response = await fetchSearchResults({
searchQuery: {
query: 'student behavior incident tracking software',
count: 5,
},
YDC_API_KEY: process.env.YDC_API_KEY,
getUserAgent: () => 'Plaited/7.x (You.com)',
})
console.log(response.results.web)
```
### Why this is the default
- cleaner than custom raw `fetch` plumbing
- better fit for repo scripts
- easier to reuse across Search/livecrawl workflows
- more robust than the raw `fetch` path we were using during Slice 14 work
## Endpoint Summary
| Endpoint | Method | URL | Use |
|---|---|---|---|
| Search | GET | `https://api.you.com/v1/agents/search` | default discovery step |
| Research | POST | `https://api.you.com/v1/research` | narrow cited synthesis |
| Contents | POST | `https://ydc-index.io/v1/contents` | explicit URL extraction |
JSON Schemas remain in `assets/`:
- [search.input.schema.json](assets/search.input.schema.json)
- [search.output.schema.json](assets/search.output.schema.json)
- [research.input.schema.json](assets/research.input.schema.json)
- [research.output.schema.json](assets/research.output.schema.json)
- [contents.input.schema.json](assets/contents.input.schema.json)
- [contents.output.schema.json](assets/contents.output.schema.json)
## Decision Rules
Use this decision tree:
1. **Need discovery, current vocabulary, or top hits?**
- use **Search**
2. **Need richer context from one or two results?**
- use **Search + livecrawl**
- or **Contents** for exact URLs
3. **Need a cited synthesized answer?**
- use **Research** only if the question is narrow and factual enough
4. **Need broad market scanning or “what models are best?”**
- do **Search first**
- then use narrower follow-up search or targeted research
## Search Patterns That Worked
Prefer:
- function-first queries
- workflow-first queries
- modern terminology over historical platform names
- targeted follow-up queries after the first search recovers better vocabulary
Examples:
- `student behavior incident tracking software`
- `reference metadata cleanup validation export workflow`
- `font library browser preview catalog`
Better flow:
1. broad discovery search
2. tighter follow-up search using recovered current terminology
3. optional livecrawl on the strongest result
## Research Usage Rules
Use `research lite` only when:
- the question is narrow
- a normal search already established the target topic
- you want a short cited synthesis
Avoid `research lite` first for:
- broad model ranking
- open-ended exploration
- many-model comparison prompts
Use `deep` only when:
- the question is high-value
- search already narrowed the topic
- and a deeper cited synthesis is still necessary
## Raw Fetch Fallback
Use raw `fetch` only when the client is not suitable:
```ts
const query = new URLSearchParams({
query: 'student behavior incident tracking workflow',
count: '3',
livecrawl: 'web',
livecrawl_formats: 'markdown',
})
const response = await fetch(`https://api.you.com/v1/agents/search?${query}`, {
headers: { 'X-API-Key': process.env.YDC_API_KEY! },
})
```
If this raw path shows transport or decompression instability in a batch script:
- switch back to the official client
- do not immediately pile on more custom retry logic
## Contents vs livecrawl
Prefer **Search + livecrawl** when:
- you still need ranking/discovery
- one or two top results likely contain enough context
Prefer **Contents** when:
- you already know the exact URL set
- you want extraction without another search step
Do not use both by default.
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.