Borrowing it
Nothing to install: this file belongs to causify-ai/helpers. 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/causify-ai/helpers/master/.claude/skills/text.summarize_hn_in_bullet_points/SKILL.mdgit clone --depth 1 https://github.com/causify-ai/helpersWrote 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/causify-ai/helpers/text.summarize_hn_in_bullet_points)<a href="https://agentmods.dev/skills/causify-ai/helpers/text.summarize_hn_in_bullet_points"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/text.summarize_hn_in_bullet_points/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/causify-ai/helpers/text.summarize_hn_in_bullet_points"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/text.summarize_hn_in_bullet_points.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 3 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00013 | $0.00376 |
| Opus 5.5 | $0.00005 | $0.00150 |
| Sonnet 5.5 | $0.00003 | $0.00075 |
| Haiku 4.5 | $0.00001 | $0.00038 |
Grade A, and why
text.summarize_hn_in_bullet_points 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.
What it actually says
Goal
- Summarize a Hacker News discussion for a given topic
- Follow the bullet point formatting rules in
.claude/skills/text.rules.md
Workflow
Read the Input
- Given a pointer to a discussion on HackerNews in the form of a URL
- E.g.,
https://news.ycombinator.com/item?id=47743628
- E.g.,
Summarize the Article
- Summarize the main article in 5 bullet points
# The peril of laziness lost - ... - ...
Summarize the Comments
-
Analyze the Hacker News comment section for the linked article
-
From all comments, summarize the 5 most interesting ones based on the following criteria:
- Thought-provoking or insightful
- Presents a unique perspective or uncommon knowledge
- Sparks discussion or debate
- Technically informative or educational
- Controversial but well-argued
- Do not print the name of the commenter
-
Avoid selecting comments that are:
- Simple jokes or memes
- Very short reactions
- Repetitive or low-effort
Write the Output
- Do not output any comment on screen
- Output the result in a file
hn.txtwithout bold or other markdown formatting - Run the command:
> lint_text.py -i hn.txt - Run the command:
> cat hn.txt
Verification
- Confirm
hn.txtwas created and contains no bold or markdown formatting - Confirm
lint_text.py -i hn.txtcompleted without errors
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 Changed · +7 lines · +2 tokens per session 09304e0e79e0
- 1mo ago First seen · 49 lines · 11 tokens per session scan A b77ee68ab872
text.summarize_hn_in_bullet_points is a skill published in the GitHub repository causify-ai/helpers (150 stars, last pushed today), licensed Apache-2.0. It adds 13 tokens to every session and 376 once invoked, about $0.0001 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 2026-09-03.
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