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AgentShelf Regex Mention Extractor
x402
AgentShelf Regex Mention Extractor is a paid API for AI agents from agentshelf.syntexa.ch, paid per call via x402, $0.009/call, status unknown (last checked 2026-10-02).
Extracts all @-mention strings from text using regex, returning up to 20 matches per call.
Price / call$0.009
Success—
StatusUnknown
How this service works
Call when an agent needs at-mentions extracted from text, capped at 20 matches. An empty match list is billed. No network. Exact $0.009 USDC. Prefer unpaid POST /v1/sandbox/regex-mention first.
Output
A list of up to 20 matched @-mention strings found in the input text, extracted via regex pattern matching. If no mentions are found, an empty list is returned — but the call is still billed at $0.009 USDC.
Example use cases
Parsing mentions from social post
“I have this tweet: 'Thanks @johnsmith and @sarahlee for the shoutout! Also ping @marketing.' — can you pull out all the @mentions from it?”
Extracting tagged users from comment
“Here's a comment from our community forum: '@mod_team please help, also tagging @alice123 and @support_bot for visibility.' Who are all the people mentioned?”
Auditing mentions in notification text
“I've got this notification body: 'You were mentioned by @ceo_jane in a thread with @hr_team and @finance_dept.' Can you list all the @handles that appear in it?”
Technical details
Endpoint
POSThttps://agentshelf.syntexa.ch/v1/regex-mention?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need fast, deterministic regex-based @mention extraction without any LLM or network overhead. It is ideal for structured pipelines processing social media text, notifications, or comments where cost predictability and speed matter. Prefer the free POST /v1/sandbox/regex-mention endpoint for testing or unpaid usage. Avoid this endpoint if your text reliably has no mentions, as empty results are still billed.
Side effects
- Empty match list returned but still billed if no @mentions are present in text
- Input text exceeds 100,000 character limit causing a validation error
- Malformed or missing 'text' field in request body causes a bad request error
- More than 20 mentions in text results in truncation at 20 matches
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | Input for this SKU. The route description says whether it is plain text, a URL, base64 bytes, or an already-encoded token. |
Tags
x402
Reviews
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