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Agent skill

Show Hn Writer

by Varnan-Tech in Varnan-Tech/opendirectory

Draft a Show HN post backed by real HN performance data. An agent skill from Varnan-Tech/opendirectory.

MITAuto-check passed

Install Show Hn Writer

skills CLI
$ npx skills add Varnan-Tech/opendirectory --skill show-hn-writer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Varnan-Tech/opendirectory show-hn-writer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Varnan-Tech/opendirectory.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/show-hn-writer .claude/skills/show-hn-writer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
show-hn-writer
GitHub stars
674
Token cost
~2.8k tokens
SKILL.md length
1,474 words
Files
6 (incl. references)
Skills in repo
61
Repo updated
First seen
Licence
MIT

At a glance

Draft a Show HN post backed by real HN performance data. An agent skill from Varnan-Tech/opendirectory.

  • Works in 8 steps: Ask the user one question before… → Determine the right post type → Draft the title → …
  • SKILL.md covers What the data says…, Step 1: Ask the user one…, Step 2: Determine the right… and Step 3: Draft the title, plus 6 more sections
  • Reaches hacker-news.firebaseio.com

What it does

Show Hn Writer is an agent skill from Varnan-Tech/opendirectory. Draft a Show HN post backed by real HN performance data. Uses observed patterns from 250 top HN posts to maximise score.

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `README.md`, `evals/evals.json` and `references/hn-rules.md`). Compatibility notes: ["claude-code","gemini-cli","github-copilot"]

The repository describes itself as: AI Agent Skills built for Founders who hate Marketing. The licence is MIT.

Example prompts

  • “/show-hn-writer”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): ["claude-code","gemini-cli","github-copilot"]

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Ask the user one question before anything else
  2. Determine the right post type
  3. Draft the title
  4. Decide whether to write a body
  5. Write the body (only if Step 4 said yes)
  6. Self-check before presenting
  7. Present output
  8. Optional — scrape current top HN posts for context

What it can do on your machine

Read from SKILL.md and the folder at commit 62e437a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • hacker-news.firebaseio.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    ["claude-code","gemini-cli","github-copilot"]

    From compatibility in the SKILL.md frontmatter.

Context cost

Show Hn Writer loads about 2.8k tokens when it runs, and up to ~4.2k if it reads all its reference files. Until then it costs about 34 tokens; SKILL.md has 1,474 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~34
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Varnan-Tech/opendirectory at commit 62e437a, republished under its MIT licence (© Varnan-Tech). 1,474 words, ~2,806 tokens.

Download SKILL.mdSave it as .claude/skills/show-hn-writer/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
show-hn-writer
description
Draft a Show HN post backed by real HN performance data. Uses observed patterns from 250 top HN posts to maximise score.
compatibility
["claude-code","gemini-cli","github-copilot"]
author
Varnan / Paras Madan
version
2.0.0
data-source
250 top HN posts scraped April 18 2026

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.

Step 1: Ask the user one question before anything else

Before drafting, ask:

"Two quick questions:

  1. Are you optimising for score (reach) or comments (discussion)?
  2. What does the project do — one sentence, technical, no adjectives?"

Do not proceed until you have both answers.

Step 2: Determine the right post type

Based on the project and goal, decide which format to use:

Plain title (recommended default) No prefix. Just what it is or what happened. Highest avg score. Use when: sharing a release, article, tool, or event.

Show HN: prefix (use sparingly) Use only when: the project is a working demo, the builder is present to answer questions, and the technical implementation is the interesting part. Avg score is low (94), but it signals authenticity when the project is genuinely novel. Always also draft a plain-title alternative for comparison.

Ask HN: prefix Use when: the goal is discussion, not promotion. Avg engagement ratio > 1.0×. Best for "who is using X?" or "should I do Y?" posts.

Tell HN: prefix Whistleblowing, accountability, or disclosure. One data point at 819 pts. Only use if the post is factual, verifiable, and the builder is named.

Step 3: Draft the title

The title is the entire post. Treat the body as optional.

Rules derived from data:

  • Target under 40 characters. Every 20 chars over that costs roughly 30 avg points.
  • Write a story, not a category. Actor + action + stakes beats noun phrases.
  • First person ("I…") adds ~100 pts avg vs plain statement when builder perspective matters.
  • No marketing adjectives. Not "fast", "simple", "powerful", "lightweight" unless it is a literal spec (e.g. "35B-A3B" is a spec, "powerful" is not).
  • Specificity beats generality. "30 WordPress plugins" beats "popular CMS plugins".
  • Year in brackets signals classic worth reading: (2008), (1956). Use when linking older content that has aged well.
  • En dash (–) for subtitle format: "Product Name – what it does". Not a hyphen (-).

Draft three variants:

  1. Shortest possible (aim for under 35 chars) — strip everything non-essential
  2. Story angle — actor + action + stakes
  3. Technical angle — lead with the interesting engineering decision

Then apply the length test: count chars on each. Flag any over 60.

Step 4: Decide whether to write a body

Ask yourself: does the technical implementation have a detail that cannot fit in the title and that HN engineers would find genuinely interesting?

If yes: write a body (see Step 5). If no: stop at the title. No body is better than a padded body.

The data shows bodies do not increase score. The only reason to write one is if the implementation is interesting enough that engineers will ask "how does this work?" and you want to pre-answer that.

Show full SKILL.md (683 more words)Show less

Step 5: Write the body (only if Step 4 said yes)

Structure — keep it tight:

Line 1: One sentence. What you built and why. First person. Not "Introducing X." Not "X is a tool that." Just: "I built X because Y."

Lines 2–4: The real reason. Honest. Specific. Was it a problem you hit yourself? Something frustrating at work? A curiosity? "I was annoyed that..." is better than "Developers often struggle with...". The builder's voice is the point.

Lines 5–8: How it actually works. This is what HN reads for. Name the specific technology choices. State the tradeoffs you made and why. One interesting engineering decision is worth more than a feature list.

Line 9: Current state in one sentence. Open source? Free? Alpha? Solo? How long you've been working on it.

Line 10: One closing sentence inviting feedback or questions. "Happy to answer questions about the implementation." / "Criticism welcome." Never ask for upvotes, shares, or sign-ups.

Hard rules:

  • 150–300 words. Under 200 is usually better.
  • First person throughout.
  • No bullet points. No headers. No bold.
  • No links in body. URL goes in the submission field.
  • No marketing words: game-changing, revolutionary, powerful, robust, seamless, innovative, best-in-class, streamline, leverage, transform, cutting-edge.

Step 6: Self-check before presenting

Run through this list. Fix anything that fails before outputting.

Title:

  • Under 60 characters (count them)
  • No marketing adjectives
  • Is it a story or a topic? (story = better)
  • First person if the builder's perspective adds something
  • No exclamation marks

Body (if written):

  • Opens with "I built…" or "For the past N months…"
  • Contains at least one specific technology name or architecture decision
  • Under 300 words
  • No links
  • Closes with feedback invitation, not call to action
  • Zero marketing words (check the list in Step 5)

Post type:

  • If using Show HN prefix: is a plain-title alternative also drafted?
  • If goal is comments: is it a question or divisive framing?
  • If goal is score: is it a statement, not a question?

Step 7: Present output

Format exactly as follows. No commentary before or after.

## HN Post

### Recommended title
[title — the shortest, strongest variant]

### Alternative titles
1. [variant 2]
2. [variant 3]

---

### Body
[body text, or "Not recommended — title is sufficient." if Step 4 said no body]

---

### Notes
- Goal: [score / comments] — based on user's answer in Step 1
- Post type used: [plain / Show HN / Ask HN / Tell HN]
- Title length: [N chars]
- Best time to post: Tuesday–Thursday, 8–10 AM US Eastern
- After posting: respond to every comment in the first two hours
- Do not share the link elsewhere for 24 hours — HN penalises vote rings

Step 8: Optional — scrape current top HN posts for context

If the user wants to check whether similar posts have been submitted recently, or wants to see what is performing in their category right now, run the scraper:

python
import requests
from concurrent.futures import ThreadPoolExecutor

HN_API = "https://hacker-news.firebaseio.com/v0"

def fetch_item(id_):
    try:
        r = requests.get(f"{HN_API}/item/{id_}.json", timeout=10)
        return r.json() if r.ok else None
    except Exception:
        return None

ids = requests.get(f"{HN_API}/topstories.json").json()[:250]
with ThreadPoolExecutor(max_workers=20) as ex:
    items = [i for i in ex.map(fetch_item, ids) if i]

# Filter by keyword relevant to the user's project
keyword = "YOUR_KEYWORD_HERE"
matches = [i for i in items if keyword.lower() in i.get("title","").lower()]

for i, item in enumerate(matches, 1):
    score = item.get("score", 0)
    title = item.get("title", "")
    by = item.get("by", "")
    print(f"{i:>2}. [{score:>4}pts] {title} — {by}")

print(f"\nTotal matching: {len(matches)}")

Use the results to:

  • Check if a near-identical post was submitted in the last 48 hours (avoid duplication)
  • See which title patterns are landing in this category right now
  • Identify the score floor for this topic area

Results are also appended to hn_log.csv automatically if the full scraper is used.

Reference: observed top performers from dataset

These are real posts from the top 250. Study the title patterns.

ScoreTitle
1941Claude Opus 4.7
1688Google broke its promise to me – now ICE has my data
1244Qwen3.6-35B-A3B: Agentic coding power, now open to all
1192Someone bought 30 WordPress plugins and planted a backdoor in all of them
1141DaVinci Resolve – Photo
990Codex for almost everything
982Stop Flock
909A new spam policy for "back button hijacking"
893GitHub Stacked PRs
819Tell HN: Fiverr left customer files public and searchable
668I wrote to Flock's privacy contact to opt out of their domestic spying program
619Measuring Claude 4.7's tokenizer costs
561God sleeps in the minerals
503Want to write a compiler? Just read these two papers (2008)

Best Show HN titles (by score): 341 | Show HN: Smol machines – subsecond coldstart, portable virtual machines 199 | Show HN: PanicLock – Close your MacBook lid disable TouchID → password unlock 187 | Show HN: Every CEO and CFO change at US public companies, live from SEC 177 | Show HN: I made a calculator that works over disjoint sets of intervals 152 | Show HN: MacMind – A transformer neural network in HyperCard on a 1989 Macintosh

Highest comment-to-score ratios (for discussion-optimised posts): 1.91× | Why is IPv6 so complicated? 1.43× | Ask HN: Building a solo business is impossible? 1.20× | Ohio prison inmates built computers and hid them in ceiling 1.13× | Ask HN: Who is using OpenClaw? 1.05× | The future of everything is lies, I guess: Where do we go from here?

© Varnan-Tech, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references) in skills/show-hn-writer of Varnan-Tech/opendirectory.

  • SKILL.md
  • .env.example
  • README.md
  • evals/evals.json
  • references/hn-rules.md
  • references/title-formulas.md

Open the folder on GitHubat commit 62e437a

Compare with similar skills

Show Hn Writer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Show Hn Writer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Show Hn Writer this skillVarnan-Tech/opendirectory674—~2.8kAutomated safety check: PassMIT
Writerjeremylongshore/tons-of-skills-marketplace2.8k—~2.1kAutomated safety check: PassMIT
Skill Writersickn33/agentic-awesome-skills47k2 repos~1.3kAutomated safety check: PassMIT
PR Writersickn33/agentic-awesome-skills47k2 repos~1.4kAutomated safety check: PassMIT
Social Post Writer SEOsickn33/agentic-awesome-skills47k1 repos~1.3kAutomated safety check: PassMIT
Documentation Writergithub/awesome-copilot40k7 repos~686Automated safety check: PassMIT

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Questions about Show Hn Writer

What does Show Hn Writer do?

Draft a Show HN post backed by real HN performance data. An agent skill from Varnan-Tech/opendirectory. Show Hn Writer is an agent skill from Varnan-Tech/opendirectory. Draft a Show HN post backed by real HN performance data.

How do I install Show Hn Writer in Claude Code?

Run `npx skills add Varnan-Tech/opendirectory --skill show-hn-writer -a claude-code`. Or copy the skill folder (skills/show-hn-writer in Varnan-Tech/opendirectory) into .claude/skills/show-hn-writer in your project. Claude Code loads it when a task matches its description.

How do I install Show Hn Writer in Codex?

Run `npx skills add Varnan-Tech/opendirectory --skill show-hn-writer -a codex`. Or copy the skill folder (skills/show-hn-writer in Varnan-Tech/opendirectory) into .agents/skills/show-hn-writer in your project. Codex loads it when a task matches its description.

Can I use Show Hn Writer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Varnan-Tech/opendirectory --skill show-hn-writer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/show-hn-writer, .gemini/skills/show-hn-writer, .github/skills/show-hn-writer and .opencode/skills/show-hn-writer in your project.

What does Show Hn Writer need to run?

SKILL.md names no scripts, command-line tools or credentials: Show Hn Writer is instructions for the agent only. Our summary lists: Python 3. Compatibility (from SKILL.md): ["claude-code","gemini-cli","github-copilot"].

Does Show Hn Writer access the network?

SKILL.md names 1 domain. In commands or code: hacker-news.firebaseio.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Show Hn Writer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Show Hn Writer use?

Show Hn Writer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Show Hn Writer use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.4k tokens, read only when the agent opens those files.

What are the alternatives to Show Hn Writer?

Skills that share tags, products or a category with Show Hn Writer: Writer (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), Skill Writer (sickn33/agentic-awesome-skills, 47k stars), PR Writer (sickn33/agentic-awesome-skills, 47k stars) and Social Post Writer SEO (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Show Hn Writer?

Varnan-Tech (a GitHub organization) maintains it in Varnan-Tech/opendirectory, which has 674 GitHub stars. The repository holds 61 skills in this directory. The repository was last updated on August 16, 2026.

Source: Varnan-Tech/opendirectory on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.