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 h4vzz/awesome-ai-agent-skills --skill webhook-setupgit clone --depth 1 https://github.com/h4vzz/awesome-ai-agent-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/h4vzz/awesome-ai-agent-skills/webhook-setup)<a href="https://agentmods.dev/skills/h4vzz/awesome-ai-agent-skills/webhook-setup"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/webhook-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/h4vzz/awesome-ai-agent-skills/webhook-setup"><img src="https://agentmods.dev/badge/skills/h4vzz/awesome-ai-agent-skills/webhook-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 | $0.00032 | $0.03759 |
| Opus 5 | $0.00016 | $0.01879 |
| Sonnet 5 | $0.00006 | $0.00752 |
| Haiku 4.5 | $0.00003 | $0.00376 |
Grade A, and why
webhook-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 10d 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.
This is a copy
97% identical to webhook-setup — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 353 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Webhook Setup
This skill enables an AI agent to build production-grade webhook receivers and configure webhook producers. The agent implements HTTP endpoints that accept event payloads, verify cryptographic signatures to authenticate senders, process events idempotently to handle retries safely, and route events by type to appropriate handlers. The result is a reliable event-driven integration that handles real-world failure modes including replay attacks, out-of-order delivery, and provider timeouts.
Workflow
-
Design the webhook endpoint: Create an HTTP POST endpoint at a stable, non-guessable URL path (e.g.,
/webhooks/stripe,/webhooks/github). The endpoint must return a200 OKresponse quickly (within 5 seconds for most providers) to acknowledge receipt—long processing should be done asynchronously via a job queue. Use HTTPS exclusively; most providers reject plain HTTP endpoints. -
Implement signature verification: Every webhook provider signs payloads using HMAC-SHA256, RSA, or a similar scheme. Before processing any event, verify the signature using the provider's signing secret. Compare signatures using a constant-time comparison function to prevent timing attacks. Reject requests with missing or invalid signatures immediately with a
401 Unauthorizedresponse. Read the raw request body for verification—parsed JSON may differ from the signed bytes. -
Parse and route events by type: Parse the verified payload and extract the event type (e.g.,
payment_intent.succeeded,push). Route each event type to a dedicated handler function using a registry or switch statement. Log unrecognized event types at warning level and return200 OKto prevent the provider from retrying unhandled events indefinitely. -
Process events idempotently: Providers retry webhook delivery when they don't receive a timely
200response, which means your handler may receive the same event multiple times. Store processed event IDs in a database table and check for duplicates before processing. Use database transactions to atomically mark an event as processed and perform its side effects.
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.
- 10d ago First seen · 353 lines · 32 tokens per session scan A 9b75d884f807
webhook-setup is a skill published in the GitHub repository h4vzz/awesome-ai-agent-skills (34 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 3,759 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to webhook-setup, differing in 2 lines, and is treated as a copy.
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