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 Varnan-Tech/opendirectory --skill noise2bloggit clone --depth 1 https://github.com/Varnan-Tech/opendirectoryWrote 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/varnan-tech/opendirectory/noise2blog)<a href="https://agentmods.dev/skills/varnan-tech/opendirectory/noise2blog"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/noise2blog/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/varnan-tech/opendirectory/noise2blog"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/noise2blog.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 29 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Supply Chain · line 99 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Data Exfiltration · line 99 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 99 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00138 | $0.02281 |
| Opus 5 | $0.00069 | $0.01141 |
| Sonnet 5 | $0.00028 | $0.00456 |
| Haiku 4.5 | $0.00014 | $0.00228 |
Grade A, and why
noise2blog scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -X POST "https://api.tavily.com/search" \ How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Noise to Blog
Take any rough input (bullet points, voice transcripts, tweet dumps, or short drafts) and produce a polished, publication-ready blog post. Every claim traces to the source material or Tavily-verified research.
Critical rule: DO NOT INVENT SPECIFICS. Every claim, metric, and example in the blog post must come from the raw input or a Tavily search result. Never fabricate data, quotes, or outcomes.
Step 1: Setup Check
Confirm required env vars are set:
echo "GEMINI_API_KEY: ${GEMINI_API_KEY:+set}"
echo "TAVILY_API_KEY: ${TAVILY_API_KEY:-not set, Tavily enrichment will be skipped}"
If GEMINI_API_KEY is missing: Stop. Tell the user: "GEMINI_API_KEY is required. Get it at aistudio.google.com → Get API key. Add it to your .env file."
If TAVILY_API_KEY is missing: Continue. Note that Tavily enrichment will be skipped. The blog post will be based entirely on the provided content. This is fine for personal stories, tutorials from experience, or opinion pieces.
Confirm input is present. The user must provide one of:
- Pasted text (bullet points, rough notes, transcript, tweet dump, short draft)
- A URL to fetch
If no input, ask: "Share your rough notes, bullet points, or transcript. Paste them directly, or give me a URL to fetch the source."
Step 2: Read and Analyze Input
If input is a URL: Fetch the page content using WebFetch. Extract: title, author, publish date, all body text, key statistics, numbered lists, subheadings, quotes.
If input is pasted text: Read it directly. Identify the input type:
- Bullet points or rough notes: fragmented ideas, incomplete sentences, stream of consciousness
- Voice transcript: conversational, repetitive, filler words (um, uh, like, you know), meandering sentences
- Tweet thread dump: short fragments, @mentions, hashtags, "1/8" numbering
- Short draft: structured but thin, needs expansion and polish
QA checkpoint: State before continuing:
- Input type detected
- Core thesis or main argument in one sentence
- The 3-5 strongest insights, facts, or ideas from the raw content
- Any claims that need external verification (benchmarks, statistics, product comparisons, research findings)
What ships with it
5 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.
- 9d ago First seen · 230 lines · 138 tokens per session scan A 69a13a864379
noise2blog is a skill published in the GitHub repository Varnan-Tech/opendirectory (635 stars, last pushed 23d ago), licensed MIT. It adds 138 tokens to every session and 2,281 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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hermes-mnemosyne
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skill-auditor
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marketplace-purchase-vetting
Use this when the user asks whether a local listing is a scam, "too good to be true," worth looking at, or a good deal. Also use this when he asks you to find options — search/discover candidates, then vet the best ones. The goal is not a generic buying guide; it is a practical risk read with clear next steps.