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 d-o-hub/github-template-ai-agents --skill secure-invite-and-accessgit clone --depth 1 https://github.com/d-o-hub/github-template-ai-agentsWrote 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/d-o-hub/github-template-ai-agents/secure-invite-and-access)<a href="https://agentmods.dev/skills/d-o-hub/github-template-ai-agents/secure-invite-and-access"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/secure-invite-and-access/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/d-o-hub/github-template-ai-agents/secure-invite-and-access"><img src="https://agentmods.dev/badge/skills/d-o-hub/github-template-ai-agents/secure-invite-and-access.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 | $0.00073 | $0.00668 |
| Opus 5 | $0.00036 | $0.00334 |
| Sonnet 5 | $0.00015 | $0.00134 |
| Haiku 4.5 | $0.00007 | $0.00067 |
Grade A, and why
secure-invite-and-access 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 8d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Secure Invite and Access
Implement access-control rules (authentication, authorization, sessions, audit logging) for any web application.
When to Use
- Working on authentication, authorization, or session management.
- Implementing role-based access control (RBAC) or permission grants.
- Updating signed URL issuance/verification or audit logging.
- Investigating auth-related bugs or observability gaps.
Workflow
- Define auth requirements -- confirm auth model (sessions, JWT, OAuth), password hashing, TTL expectations.
- Threat model -- identify enumeration risks, replay attacks, session leakage vectors.
- Implement -- secure password hashing (Argon2id/bcrypt), session issuing/refresh/revoke, signed URLs with TTL, trace ID logging.
- Audit -- log auth events with actor + trace ID. Return generic access-denied errors; never leak whether accounts exist.
- Tests -- add coverage for password validation, session expiry, signature validation, revocation flows.
Checklist
- All auth endpoints validate payloads with schema validation + capability checks.
- Sessions + signed tokens include expiry metadata and trace IDs.
- Logout/refresh revoke existing tokens.
- Audit rows created for create/update/revoke/grant usage.
- Rate limiting or abuse guard documented (even if stubbed).
- Never expose whether an email/username exists in error messages.
See Also
security-code-auditor— Security auditsprivacy-first— Email/personal data prevention
Rationalizations
| Rationalization | Reality |
|---|---|
| "Auth is straightforward, I don't need a dedicated skill" | Authentication bugs are among the most critical security vulnerabilities; systematic patterns prevent common mistakes. |
| "I'll add rate limiting later" | Rate limiting is a core auth control, not an afterthought; abuse vectors are most effective before protections exist. |
| "Generic error messages are用户体验bad" | leaking account existence is a security vulnerability; generic errors are an industry-standard requirement. |
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 67 lines · 73 tokens per session scan A fd15fa80dcff
secure-invite-and-access is a skill published in the GitHub repository d-o-hub/github-template-ai-agents (2 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 668 once invoked, about $0.0004 per session on Opus 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 2026-08-31.
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