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 zytelabs/claude-webscraping-skills --skill parsergit clone --depth 1 https://github.com/zytelabs/claude-webscraping-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/zytelabs/claude-webscraping-skills/parser)<a href="https://agentmods.dev/skills/zytelabs/claude-webscraping-skills/parser"><img src="https://agentmods.dev/badge/skills/zytelabs/claude-webscraping-skills/parser.svg" alt="Measured on agentmods" 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 | $0.00030 | $0.00306 |
| Opus 5 | $0.00015 | $0.00153 |
| Sonnet 5 | $0.00006 | $0.00061 |
| Haiku 4.5 | $0.00003 | $0.00031 |
Grade A, and why
parser 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.
What it actually says
Parser
Extract structured product data from raw HTML. Tries JSON-LD first via Extruct, falls back to CSS selectors via Parsel.
When to use
Use this skill when you have raw HTML and need to extract structured data from it — product details, prices, specs, ratings, or any page content.
Instructions
- Save the HTML to a temporary file
page.html - Run
parser.pyagainst it:python parser.py page.html - The script outputs a JSON object. Check the
methodfield:"extruct"— clean structured data was found, use it directly"parsel"— fell back to CSS selectors, review fields for completeness
- If key fields are missing from the Parsel output, ask the user which fields they need and re-run with
--fields:python parser.py page.html --fields "price,rating,brand" - Return the parsed JSON to the conversation for use in the Compare skill.
Notes
- Always prefer the Extruct path — it is more stable and requires no maintenance
- Parsel selectors are generated heuristically and may need adjustment for unusual page layouts
- Run once per page; pass all outputs together into the Compare skill
What ships with it
2 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 · 32 lines · 30 tokens per session scan A 33c71822c794
parser is a skill published in the GitHub repository zytelabs/claude-webscraping-skills (6 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 306 once invoked, about $0.0002 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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