Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add autohandai/community-skills --skill authentication-setupgit clone --depth 1 https://github.com/autohandai/community-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/autohandai/community-skills/authentication-setup)<a href="https://agentmods.dev/skills/autohandai/community-skills/authentication-setup"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/authentication-setup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/autohandai/community-skills/authentication-setup"><img src="https://agentmods.dev/badge/skills/autohandai/community-skills/authentication-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.04645 |
| Opus 5.5 | $0.00018 | $0.01858 |
| Sonnet 5.5 | $0.00009 | $0.00929 |
| Haiku 4.5 | $0.00004 | $0.00464 |
Grade A, and why
authentication-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 667 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Authentication Setup
When to use this skill
Lists specific situations where this skill should be triggered:
- User Login System: When adding user authentication to a new application
- API Security: When adding an authentication layer to a REST or GraphQL API
- Permission Management: When role-based access control is needed
- Authentication Migration: When migrating an existing auth system to JWT or OAuth
- SSO Integration: When integrating social login with Google, GitHub, Microsoft, etc.
Input Format
The required and optional input information to collect from the user:
Required Information
- Authentication Method: Choose from JWT, Session, or OAuth 2.0
- Backend Framework: Express, Django, FastAPI, Spring Boot, etc.
- Database: PostgreSQL, MySQL, MongoDB, etc.
- Security Requirements: Password policy, token expiry times, etc.
Optional Information
- MFA Support: Whether to enable 2FA/MFA (default: false)
- Social Login: OAuth providers (Google, GitHub, etc.)
- Session Storage: Redis, in-memory, etc. (if using sessions)
- Refresh Token: Whether to use (default: true)
Input Example
Build a user authentication system:
- Auth method: JWT
- Framework: Express.js + TypeScript
- Database: PostgreSQL
- MFA: Google Authenticator support
- Social login: Google, GitHub
- Refresh Token: enabled
Instructions
Specifies the step-by-step task sequence to follow precisely.
Step 1: Design the Data Model
Design the database schema for users and authentication.
Tasks:
- Design the User table (id, email, password_hash, role, created_at, updated_at)
- RefreshToken table (optional)
- OAuthProvider table (if using social login)
- Never store passwords in plaintext (bcrypt/argon2 hashing is mandatory)
Example (PostgreSQL):
CREATE TABLE users (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
email VARCHAR(255) UNIQUE NOT NULL,
password_hash VARCHAR(255), -- NULL if OAuth only
role VARCHAR(50) DEFAULT 'user',
is_verified BOOLEAN DEFAULT false,
mfa_secret VARCHAR(255),
created_at TIMESTAMP DEFAULT NOW(),
updated_at TIMESTAMP DEFAULT NOW()
);
CREATE TABLE refresh_tokens (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
user_id UUID REFERENCES users(id) ON DELETE CASCADE,
token VARCHAR(500) UNIQUE NOT NULL,
expires_at TIMESTAMP NOT NULL,
created_at TIMESTAMP DEFAULT NOW()
);
CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_refresh_tokens_user_id ON refresh_tokens(user_id);
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 667 lines · 44 tokens per session scan A 3c612477d65b
authentication-setup is a skill published in the GitHub repository autohandai/community-skills (12 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 44 tokens to every session and 4,645 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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