Borrowing it
Nothing to install: this file belongs to aboul3ata/lazyweb-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/aboul3ata/lazyweb-skill/main/CLAUDE.mdgit clone --depth 1 https://github.com/aboul3ata/lazyweb-skillWrote 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/instructions/aboul3ata/lazyweb-skill/claude-md)<a href="https://agentmods.dev/instructions/aboul3ata/lazyweb-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/aboul3ata/lazyweb-skill/claude-md/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/instructions/aboul3ata/lazyweb-skill/claude-md"><img src="https://agentmods.dev/badge/instructions/aboul3ata/lazyweb-skill/claude-md.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 | $0.01050 | $0.01050 |
| Opus 5.5 | $0.00420 | $0.00420 |
| Sonnet 5.5 | $0.00210 | $0.00210 |
| Haiku 4.5 | $0.00105 | $0.00105 |
Grade A, and why
lazyweb-skill CLAUDE.md 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 — 22 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lazyweb skill pack — agent guidance
Lazyweb report principles (governs any agent building a Lazyweb report)
Every Lazyweb skill produces an HTML report. Whatever the skill, the report must embody these four principles — they are the product, not a style preference.
-
Show, don't tell. Prove every claim with a real visual reference or data, never prose alone. Each assertion (pattern, anti-pattern, idea, hypothesis, "what's working", convention check, recommendation, A/B learning) carries the screenshot(s)/experiment that demonstrate it, sitting with the claim. When 2+ references support one claim, render a
.decksnap-carousel — a horizontally-scrolling strip that snaps card-to-card with ◀ ▶ prev/next buttons — never a bullet list or a cross-reference to another section. Quantify prevalence ("5 of 9 references") instead of asserting it ("near-universal"). Never render a proposed layout as ASCII/box-drawing<pre>art — use an HTML/CSS mock-frame or a generated image. -
Be opinionated; carry the decision. Take a clear ranked stance and lead with a single recommended path, marked as such in the human-visible body (not only in the machine handoff block). Tell the user what to do first and what to skip, with a one-line reason each. Never hand over an undifferentiated menu of co-equal options and make the reader choose.
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Maximize confidence with evidence. Back each recommendation with what worked for OTHER apps (real screenshots) PLUS supporting data — prevalence across the corpus, and A/B experiment learnings for growth/monetization screens. When experiment data is unavailable, say so and fall back to a stated prevalence count; never ship a recommendation with no visual and no number behind it.
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Be truth-seeking. Never overclaim. Label evidence strength honestly (measured vs directional vs single-source/off-category) on each claim, and flag a weak, thin, single-source, or context-mismatched corpus up front. Tag any brand inferred from a URL/vision description as unverified. Never fabricate a reference, a metric, or a company name. The machine-readable handoff and the human-facing body must agree about confidence.
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 · 22 lines · 1,050 tokens per session scan A 580d8a981048
lazyweb-skill CLAUDE.md is an instructions file published in the GitHub repository aboul3ata/lazyweb-skill (455 stars, last pushed 26d ago), licensed MIT. It adds 1,050 tokens to every session, about $0.0042 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 2026-08-30.
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