external/tgd-skills/tgd-api-and-interface-design/SKILL.md
Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
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Design stable, well-documented interfaces that are hard to misuse. Good interfaces make the right thing easy and the wrong thing hard. This applies to REST APIs, GraphQL schemas, module boundaries, component props, and any surface where one piece of code talks to another.
With a sufficient number of users of an API, all observable behaviors of your system will be depended on by somebody, regardless of what you promise in the contract.
This means: every public behavior — including undocumented quirks, error message text, timing, and ordering — becomes a de facto contract once users depend on it. Design implications:
tgd-deprecation-and-migration for how to safely remove things users depend on.Avoid forcing consumers to choose between multiple versions of the same dependency or API. Diamond dependency problems arise when different consumers need different versions of the same thing. Design for a world where only one version exists at a time — extend rather than fork.
Define the interface before implementing it. The contract is the spec — implementation follows.
// Define the contract first
interface TaskAPI {
// Creates a task and returns the created task with server-generated fields
createTask(input: CreateTaskInput): Promise<Task>;
// Returns paginated tasks matching filters
listTasks(params: ListTasksParams): Promise<PaginatedResult<Task>>;
// Returns a single task or throws NotFoundError
getTask(id: string): Promise<Task>;
// Partial update — only provided fields change
updateTask(id: string, input: UpdateTaskInput): Promise<Task>;
// Idempotent delete — succeeds even if already deleted
deleteTask(id: string): Promise<void>;
}
Pick one error strategy and use it everywhere:
// REST: HTTP status codes + structured error body
// Every error response follows the same shape
interface APIError {
error: {
code: string; // Machine-readable: "VALIDATION_ERROR"
message: string; // Human-readable: "Email is required"
details?: unknown; // Additional context when helpful
};
}
// Status code mapping
// 400 → Client sent invalid data
// 401 → Not authenticated
// 403 → Authenticated but not authorized
// 404 → Resource not found
// 409 → Conflict (duplicate, version mismatch)
// 422 → Validation failed (semantically invalid)
// 500 → Server error (never expose internal details)
Don't mix patterns. If some endpoints throw, others return null, and others return { error } — the consumer can't predict behavior.
Trust internal code. Validate at system edges where external input enters:
// Validate at the API boundary
app.post('/api/tasks', async (req, res) => {
const result = CreateTaskSchema.safeParse(req.body);
if (!result.success) {
return res.status(422).json({
error: {
code: 'VALIDATION_ERROR',
message: 'Invalid task data',
details: result.error.flatten(),
},
});
}
// After validation, internal code trusts the types
const task = await taskService.create(result.data);
return res.status(201).json(task);
});
Where validation belongs:
Third-party API responses are untrusted data. Validate their shape and content before using them in any logic, rendering, or decision-making. A compromised or misbehaving external service can return unexpected types, malicious content, or instruction-like text.
Where validation does NOT belong:
Extend interfaces without breaking existing consumers:
// Good: Add optional fields
interface CreateTaskInput {
title: string;
description?: string;
priority?: 'low' | 'medium' | 'high'; // Added later, optional
labels?: string[]; // Added later, optional
}
// Bad: Change existing field types or remove fields
interface CreateTaskInput {
title: string;
// description: string; // Removed — breaks existing consumers
priority: number; // Changed from string — breaks existing consumers
}
| Pattern | Convention | Example |
|---------|-----------|---------|
| REST endpoints | Plural nouns, no verbs | GET /api/tasks, POST /api/tasks |
| Query params | camelCase | ?sortBy=createdAt&pageSize=20 |
| Response fields | camelCase | { createdAt, updatedAt, taskId } |
| Boolean fields | is/has/can prefix | isComplete, hasAttachments |
| Enum values | UPPER_SNAKE | "IN_PROGRESS", "COMPLETED" |
GET /api/tasks → List tasks (with query params for filtering)
POST /api/tasks → Create a task
GET /api/tasks/:id → Get a single task
PATCH /api/tasks/:id → Update a task (partial)
DELETE /api/tasks/:id → Delete a task
GET /api/tasks/:id/comments → List comments for a task (sub-resource)
POST /api/tasks/:id/comments → Add a comment to a task
Paginate list endpoints:
// Request
GET /api/tasks?page=1&pageSize=20&sortBy=createdAt&sortOrder=desc
// Response
{
"data": [...],
"pagination": {
"page": 1,
"pageSize": 20,
"totalItems": 142,
"totalPages": 8
}
}
Use query parameters for filters:
GET /api/tasks?status=in_progress&assignee=user123&createdAfter=2025-01-01
Accept partial objects — only update what's provided:
// Only title changes, everything else preserved
PATCH /api/tasks/123
{ "title": "Updated title" }
// Good: Each variant is explicit
type TaskStatus =
| { type: 'pending' }
| { type: 'in_progress'; assignee: string; startedAt: Date }
| { type: 'completed'; completedAt: Date; completedBy: string }
| { type: 'cancelled'; reason: string; cancelledAt: Date };
// Consumer gets type narrowing
function getStatusLabel(status: TaskStatus): string {
switch (status.type) {
case 'pending': return 'Pending';
case 'in_progress': return `In progress (${status.assignee})`;
case 'completed': return `Done on ${status.completedAt}`;
case 'cancelled': return `Cancelled: ${status.reason}`;
}
}
// Input: what the caller provides
interface CreateTaskInput {
title: string;
description?: string;
}
// Output: what the system returns (includes server-generated fields)
interface Task {
id: string;
title: string;
description: string | null;
createdAt: Date;
updatedAt: Date;
createdBy: string;
}
type TaskId = string & { readonly __brand: 'TaskId' };
type UserId = string & { readonly __brand: 'UserId' };
// Prevents accidentally passing a UserId where a TaskId is expected
function getTask(id: TaskId): Promise<Task> { ... }
| Rationalization | Reality | |---|---| | "We'll document the API later" | The types ARE the documentation. Define them first. | | "We don't need pagination for now" | You will the moment someone has 100+ items. Add it from the start. | | "PATCH is complicated, let's just use PUT" | PUT requires the full object every time. PATCH is what clients actually want. | | "We'll version the API when we need to" | Breaking changes without versioning break consumers. Design for extension from the start. | | "Nobody uses that undocumented behavior" | Hyrum's Law: if it's observable, somebody depends on it. Treat every public behavior as a commitment. | | "We can just maintain two versions" | Multiple versions multiply maintenance cost and create diamond dependency problems. Prefer the One-Version Rule. | | "Internal APIs don't need contracts" | Internal consumers are still consumers. Contracts prevent coupling and enable parallel work. |
/api/createTask, /api/getUsers)After designing an API:
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
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