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 AgriciDaniel/claude-repurpose --skill repurpose-quoragit clone --depth 1 https://github.com/AgriciDaniel/claude-repurposeWrote 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/agricidaniel/claude-repurpose/repurpose-quora)<a href="https://agentmods.dev/skills/agricidaniel/claude-repurpose/repurpose-quora"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-repurpose/repurpose-quora/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/agricidaniel/claude-repurpose/repurpose-quora"><img src="https://agentmods.dev/badge/skills/agricidaniel/claude-repurpose/repurpose-quora.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 | $0.00095 | $0.02019 |
| Opus 5 | $0.00048 | $0.01009 |
| Sonnet 5 | $0.00019 | $0.00404 |
| Haiku 4.5 | $0.00010 | $0.00202 |
Grade A, and why
repurpose-quora 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 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.
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 — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quora Content Generator
Produce a detailed answer, a Quora Space post, and question suggestions from the content atoms provided by the orchestrator.
Inputs
Received from the parent agent (repurpose-longform):
| Input | Description |
|---|---|
atoms |
Full list of content atoms with types and impact ratings |
main_argument |
One-sentence thesis of the source content |
target_audience |
Who benefits from this content |
primary_topic |
Category or niche |
voice_profile |
Detected or overridden brand voice |
brief_mode |
If true, produce answer only (skip Space post and questions) |
References
Load before generating:
references/platform-specs.md-- Quora character limits, posting times, algorithm weightsreferences/voice-adaptation.md-- Quora tone rules (expert, evidence-based)references/hook-formulas.md-- opening hooks for answers and Space posts
Core Principle: Authority Through Depth
Quora rewards expertise, not marketing. The platform's algorithm and community both prioritize thorough, evidence-based answers over shallow or promotional content.
What this means for output:
- The answer must be complete and standalone -- a reader should learn everything they need without clicking any link
- Lead with direct answers, not preamble. Quora readers are impatient with "great question!" openings.
- Credentials and specificity build trust. "After analyzing 200 campaigns..." beats "In my experience..."
- Google indexes Quora answers heavily -- treat every answer as a mini SEO landing page
- One external link maximum per answer, placed naturally in context or at the bottom
- Never use phrases like "check out my article" or "I wrote about this on my blog"
- Instead: "I covered the full methodology with data here: [link]" (if the link adds genuine value)
Output 1: Answer
File: quora/answer.md
Question
Derive the best question to answer from the content atoms. The question should be:
- Something a real Quora user would actually search for or ask
- Specific enough to have a clear answer, broad enough to attract traffic
- Aligned with the strongest atoms (especially
insight,stat,howto)
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 · 209 lines · 95 tokens per session scan A bb5f953f15a7
repurpose-quora is a skill published in the GitHub repository AgriciDaniel/claude-repurpose (146 stars, last pushed 5mo ago), licensed MIT. It adds 95 tokens to every session and 2,019 once invoked, about $0.0005 per session on Opus 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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