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 show-hn-writergit 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/show-hn-writer)<a href="https://agentmods.dev/skills/varnan-tech/opendirectory/show-hn-writer"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/show-hn-writer/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/show-hn-writer"><img src="https://agentmods.dev/badge/skills/varnan-tech/opendirectory/show-hn-writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00034 | $0.02844 |
| Opus 5 | $0.00017 | $0.01422 |
| Sonnet 5 | $0.00007 | $0.00569 |
| Haiku 4.5 | $0.00003 | $0.00284 |
Grade A, and why
show-hn-writer 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 11d 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.
r = requests.get(f"{HN_API}/item/{id_}.json", timeout=10) How it starts
The opening of the file, as written. The whole thing — 303 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Show HN Writer — Data-Backed Edition
This skill drafts HN posts using patterns extracted from 250 real top-ranking posts. Every rule below comes from observed data, not convention.
What the data says (internalize this before writing anything)
These are the findings from 250 top HN posts scraped April 18 2026. They override any received wisdom about HN writing.
Title length is the single strongest predictor of score.
- Under 40 chars: avg 248 pts (n=82)
- 40–59 chars: avg 192 pts (n=68)
- 60–79 chars: avg 150 pts (n=91)
- 80+ chars: avg 131 pts (n=9) Default target: under 40 characters. Hard ceiling: 60.
Body text does not affect score. 90% of posts had no body. With-body avg: 189. Without-body avg: 193. Statistically identical. A body is only worth writing if you have genuinely interesting technical detail that won't fit in a title. Never write a body to pad credibility.
Show HN prefix suppresses score. Show HN posts averaged 94 pts vs 186+ for plain statements. The label signals "I want feedback on my thing" which triggers a more skeptical read. Only use "Show HN:" when the project is genuinely novel. Always offer a plain-title alternative.
First-person titles outperform anonymous statements. First-person ("I…", "My…", "We…"): avg 291 pts (n=9). Plain statement: avg 186 pts (n=126). If the builder's perspective is part of the story, lead with it.
Questions generate comments more than upvotes. Question titles avg ratio of comments-to-score above 1.0×. Best for discussions, not for raw score. Ask the user which they're optimising for before writing.
Themes that consistently outperform:
- Security / backdoor / breach stories: avg 308 pts
- Privacy / surveillance / data stories: avg 282 pts
- AI / LLM releases: avg 266 pts (42 posts — largest category)
- Open source releases: avg 485 pts (small n, but strong signal)
The highest-scoring titles share one trait: they are stories, not topics. "Someone bought 30 WordPress plugins and planted a backdoor in all of them" — 1192 pts. "Google broke its promise to me – now ICE has my data" — 1688 pts. A topic is "WordPress plugin security". A story has an actor, an action, and stakes.
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.
- 11d ago First seen · 303 lines · 34 tokens per session scan A 68a10ca45eaa
show-hn-writer is a skill published in the GitHub repository Varnan-Tech/opendirectory (637 stars, last pushed 24d ago), licensed MIT. It adds 34 tokens to every session and 2,844 once invoked, about $0.0002 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.
Other skills, from other repositories
content-style
Writing Reddit-native content that sounds human, avoids AI tells, and delivers value through structure and specificity. Applies to workshop posts, definitive model guides, research megathreads, and community FYI/update posts.
coding-worktree-recovery
Use this skill when coding-agent work is interrupted, an agent exits without a clean commit, multiple controllers target the same checkout, or the checkout produces inconsistent file/Git behavior.
macos-storage-management
Safely reclaim local Mac storage without mistaking cloud placeholders for resident data, losing File Provider content, or flattening metadata onto an incompatible external filesystem.
hermes-mnemosyne
Mnemosyne is Hermes' primary local-first memory engine — SQLite with vector + FTS5 hybrid search, 19+ tools, auto-consolidation, and a standalone CLI. It's a pip-installed plugin (not a built-in toolset) discovered via $HERMESHOME/plugins/mnemosyne/.
skill-auditor
Audit any Hermes skill file and assign a quality grade based on clarity, completeness, tool guidance, and shareability. Returns specific fix suggestions ranked by impact.
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.