documentation
Creates, structures, and reviews technical documentation following the Diátaxis framework (tutorials, how-to guides, reference, and explanation pages). Use when a user needs to write or reorganize docs, structure a tutorial vs. a how-to guide, build reference docs or API documentation, create explanation pages, choose between Diátaxis documentation types, or improve existing documentation structure. Trigger terms include: documentation structure, Diátaxis, tutorials vs how-to guides, organize docs, user guide, reference docs, technical writing.
What this skill does
## When to use
Use this skill when you need to create, review, or improve technical documentation following the Diátaxis framework. Examples include:
- Creating user guides
- API documentation
- Tutorial content
- Restructuring existing documentation to better serve different user needs and contexts
## Instructions
Organize documentation into four distinct types — tutorials, how-to guides, reference material, and explanations — each serving different user needs and contexts.
Always ask clarifying questions about the user's context, audience, and goals **before** creating documentation.
---
### Step 1 — Identify the documentation type
Use the following decision checklist based on user signals:
| User signal | Documentation type |
|---|---|
| "I'm new to X and want to learn it" / "walk me through" | **Tutorial** |
| "How do I…?" / "I need to accomplish X" | **How-to guide** |
| "What are the parameters/options/syntax for X?" | **Reference** |
| "Why does X work this way?" / "Help me understand X" | **Explanation** |
Quick decision tree:
- Is the user **learning by doing** for the first time? → Tutorial
- Do they need to **solve a specific problem** they already understand? → How-to guide
- Do they need **technical facts** to look up? → Reference
- Do they want **conceptual background**? → Explanation
---
### Step 2 — Apply type-specific patterns
#### Tutorials (learning-oriented)
- **Title pattern:** Start with a verb — *"Build your first X"*, *"Create a Y from scratch"*
- Structure: Goal → Prerequisites → Numbered steps → Immediate verifiable result at each step → Final outcome
- Minimise explanation; maximise doing
- Every step must produce a visible, testable result
- **Validation:** A beginner must be able to complete the tutorial without external help
**Example intro:**
> *"In this tutorial, you will build a simple REST API using Express. By the end, you will have a running server that responds to GET requests. No prior Express experience is needed."*
---
#### How-to guides (problem-oriented)
- **Title pattern:** Frame as a task — *"How to configure X"*, *"How to deploy Y to Z"*
- Structure: Goal statement → Assumptions/prerequisites → Numbered steps → Expected result
- Assume baseline knowledge; skip conceptual explanations
- Allow for variation; note alternatives where they exist
- **Validation:** An experienced user can complete the task without confusion or backtracking
**Example intro:**
> *"This guide shows how to add JWT authentication to an existing Express app. It assumes you have a working Express server and basic familiarity with middleware."*
---
#### Reference (information-oriented)
- **Title pattern:** Name the thing — *"Configuration options"*, *"API endpoints"*, *"CLI flags"*
- Structure: Consistent repeatable format per entry (name → type → default → description → example)
- State facts; avoid instruction beyond minimal usage examples
- Keep current; version-stamp if needed
- **Validation:** A user can look up a specific fact in under 30 seconds without reading surrounding content
**Example entry:**
> **`timeout`** *(integer, default: `5000`)*
> Maximum time in milliseconds to wait for a response before the request fails.
> *Example:* `{ timeout: 3000 }`
---
#### Explanations (understanding-oriented)
- **Title pattern:** Frame as a concept — *"How X works"*, *"Understanding Y"*, *"Why Z is designed this way"*
- Structure: Context → Core concept → Alternatives/trade-offs → Higher-level perspective
- Avoid step-by-step instruction or technical specification
- **Validation:** After reading, the user can explain the concept in their own words and understands the rationale behind design decisions
**Example intro:**
> *"Authentication and authorisation are often confused. This page explains the distinction, why both matter, and how common patterns (sessions, tokens, OAuth) approach each concern differently."*
---
### Step 3 — Maintain separation and integration
- Keep each document a single type — don't mix tutorial steps with reference tables or conceptual digressions
- Cross-link between types: a tutorial can link to the relevant reference page; a how-to guide can link to an explanation for background
- Use consistent headings and terminology across all types so users can navigate the full documentation system
---
### Step 4 — Validate before delivering
| Type | Validation check |
|---|---|
| Tutorial | Can a beginner complete it end-to-end without external help? |
| How-to guide | Does it solve the stated problem for an experienced user? |
| Reference | Can the user find a specific fact in under 30 seconds? |
| Explanation | Does the user understand the *why*, not just the *what*? |
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.