blueprints-writing

Included with Lifetime

$97 forever

Use when creating or updating technical blueprint documentation for new features, API changes, or architectural modifications. Always search existing blueprints first to avoid duplication, then write with proper structure.

Backend & APIs

What this skill does


# Writing Technical Blueprints

## Purpose

Technical blueprints document **how systems work internally**. They differ from user documentation (how to use) and README files (project overview).

## When to Write Blueprints

Write blueprints for:

- Complex systems with multiple components
- Public APIs and their contracts
- Architecture decisions and their rationale
- Behavior that isn't obvious from code
- Integration points between systems

Skip blueprints for:

- Self-documenting code (simple utilities)
- Test files (tests ARE the documentation)
- External dependencies (link to their docs)

## Creating Blueprints

**IMPORTANT:** Always check for existing blueprints before creating new ones, and use the proper frontmatter format.

```
# 1. List existing blueprints
Glob("blueprints/*.md")

# 2. Search for related blueprints by keyword
Grep("keyword", path: "blueprints/", output_mode: "files_with_matches")

# 3. Read existing blueprint if updating
Read("blueprints/authentication.md")

# 4. Write the blueprint with frontmatter
Write("blueprints/system-name.md", content_with_frontmatter)
```

The frontmatter format is:

```yaml
---
name: system-name
summary: Brief one-line description
---
```

## Blueprint File Structure

Use this structure for blueprint content:

```markdown
---
name: system-name
summary: One-line description of what this system does.
---

# System Name

One-line description of what this system does.

## Overview

2-3 paragraphs covering:
- Why this system exists (problem it solves)
- What it does at a high level
- Where it fits in the larger architecture

## Architecture

### Components

List major components:
- **ComponentA** - Purpose and responsibility
- **ComponentB** - Purpose and responsibility

### Data Flow

Describe how data moves through the system:
1. Input arrives via X
2. ComponentA processes and transforms
3. Result passed to ComponentB
4. Output returned/stored

### Dependencies

- **Dependency** - Why it's needed, what it provides

## API / Interface

### Functions

#### `functionName(param1, param2)`

Clear description of what the function does.

**Parameters:**
- `param1` (Type) - What this parameter controls
- `param2` (Type, optional) - Default behavior if omitted

**Returns:** Type - Description of return value

**Throws:** ErrorType - When this error occurs

**Example:**
```typescript
const result = functionName('value', { option: true });
```

### Configuration

| Option | Type | Default | Description |
|--------|------|---------|-------------|
| `optionA` | boolean | false | What it controls |

## Behavior

### Normal Operation

Step-by-step description of typical execution flow.

### Error Handling

How the system responds to:

- Invalid input
- Missing dependencies
- External failures

### Edge Cases

Document non-obvious behaviors:

- Empty input handling
- Concurrent access
- Resource limits

## Files

Key files and their roles:

- `src/main.ts:1-50` - Entry point, initialization
- `src/processor.ts` - Core processing logic
- `src/types.ts` - Type definitions

## Related Systems

Example format:

```markdown
- [Related System](./related-system.md) - How they interact
```
```

## Writing Style

### Be Precise

Bad: "The system handles errors gracefully"
Good: "Invalid input returns a ValidationError with the field name and reason"

### Document Behavior, Not Implementation

Bad: "Uses a for loop to iterate through items"
Good: "Processes items sequentially, stopping at the first failure"

### Include Examples

Show, don't just tell:
```typescript
// Good: concrete example
const result = processItems(['a', 'b', 'c'], { parallel: true });
// Returns: { processed: 3, failed: 0 }
```

### Keep Current

- Update blueprints alongside code changes
- Remove documentation for deleted features
- Mark deprecated features clearly

## Common Mistakes

1. **Too much detail** - Don't document every line of code
2. **Too little context** - Explain why, not just what
3. **Stale documentation** - Outdated docs are worse than none
4. **Duplicate content** - Link instead of copying
5. **Implementation focus** - Document contracts, not internals

Files: 1

Size: 4.4 KB

Complexity: 13/100

Category: Backend & APIs

Source: https://github.com/thebushidocollective/han/tree/main/plugins/tools/blueprints/skills/blueprints-writing

Related in Backend & APIs

jfrog

Included

Interact 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.

Backend & APIsscripts

cupynumeric-migration-readiness

Included

Pre-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.

Backend & APIsscripts

alibabacloud-data-agent-skill

Included

Invoke 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".

Backend & APIsscripts

token-optimizer

Included

Reduce 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.

Backend & APIsscripts

resend-cli

Included

Use 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.

Backend & APIsscripts

alibabacloud-odps-maxframe-coding

Included

Use 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.

Backend & APIsscripts