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 TaplioOfficial/taplio-linkedin-plugin --skill linkedin-viral-post-analyzergit clone --depth 1 https://github.com/TaplioOfficial/taplio-linkedin-pluginWrote 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/taplioofficial/taplio-linkedin-plugin/linkedin-viral-post-analyzer)<a href="https://agentmods.dev/skills/taplioofficial/taplio-linkedin-plugin/linkedin-viral-post-analyzer"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-plugin/linkedin-viral-post-analyzer/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/taplioofficial/taplio-linkedin-plugin/linkedin-viral-post-analyzer"><img src="https://agentmods.dev/badge/skills/taplioofficial/taplio-linkedin-plugin/linkedin-viral-post-analyzer.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 | $0.00089 | $0.01401 |
| Opus 5 | $0.00044 | $0.00700 |
| Sonnet 5 | $0.00018 | $0.00280 |
| Haiku 4.5 | $0.00009 | $0.00140 |
Grade B, and why
linkedin-viral-post-analyzer scanned grade B 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 10d 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.
Subtle steeringmediumPrompt injection
Instructions that bias recommendations or shape behaviour without the user noticing.
- Never recommend the user copy verbatim. Always extract the structure. This is a copy
100% identical to linkedin-viral-post-analyzer — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Viral Post Analyzer
Reverse-engineer the post. Steal the architecture, ship your own substance.
When to trigger
The user pastes a LinkedIn post and says "why did this work ?", "analyze this viral post", "I want to write something like this", "give me the template".
Inputs to ask for
- The full post text.
- The performance numbers if available (impressions, likes, comments, shares).
- The author's typical baseline (so you can spot what made THIS post outperform).
- Optional : the time of day / day of week it was posted.
Process
- Score the post on 7 dimensions :
- Hook strength : does line 1 stop the scroll ?
- Structure : is it scannable ? Where is the white space ?
- Emotional driver : curiosity, anger, validation, hope, status, fear ?
- Specificity : real names, real numbers, real dates ?
- Audience match : does it talk to one specific person, not "everyone" ?
- CTA : does it earn the comment / share / save ?
- Format : text, list, story, contrarian take, screenshot, image ?
- Identify the 2 to 3 levers that did the heavy lifting. Not 7 levers, just the load-bearing ones.
- Strip the post down to its template : replace the substance with placeholders so the user can plug in their own topic.
Output format
POST AT A GLANCE
Author angle : [what they typically post about]
Performance : [numbers, or "above their baseline" if unknown]
Format : [story / list / opinion / contrarian / etc.]
WHAT WORKED (the load-bearing levers)
1. [lever 1 with specific quote from the post]
2. [lever 2 with specific quote]
3. [lever 3 with specific quote, optional]
WHAT DID NOT MATTER
[2-3 things that look important but were not, e.g. "post length", "emojis", "time of day"]
THE REUSABLE TEMPLATE
[
Hook : [pattern]
Setup : [pattern]
Twist : [pattern]
Payoff : [pattern]
CTA : [pattern]
]
HOW TO USE THIS TEMPLATE FOR YOUR NEXT POST
[3 specific topics from the user's world that fit this template]
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.
- 10d ago First seen · 93 lines · 89 tokens per session scan B a0918245c558
linkedin-viral-post-analyzer is a skill published in the GitHub repository TaplioOfficial/taplio-linkedin-plugin (2 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 1,401 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (subtle steering). It is 100% identical to linkedin-viral-post-analyzer, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
youtube-producer
Plans, packages, and scripts long-form video for retention and channel growth — idea selection, titles and thumbnails, script structure, and diagnosing why a video or channel underperforms. Use this for video ideas, packaging, scripting, a retention teardown, or channel strategy — including when someone describes a…
ai-ml-governance
Governs models and AI systems in production — intended use, evaluation, monitoring, human oversight, documentation, and the decision to deploy or retire. Use this before deploying a model or AI feature, when defining evaluation criteria, when a model's behavior has drifted, when assessing AI risk or regulatory…
paid-advertising
Plans, runs, and optimizes paid acquisition across search, social, and display — account structure, targeting, creative, bidding, budget, and the analysis that says whether to scale or stop. Use this to set up or restructure campaigns, write and iterate ad creative, diagnose rising costs or falling performance, decide…
customer-onboarding-and-implementation
Takes a new customer from signature to working — setting a definition of live that both sides agreed before the contract was signed, planning and staffing the implementation, running data migration and integration realistically, training the people who will actually use it, and handing over to the ongoing…
financial-statement-analysis
Reads a set of financial statements and establishes what changed and why — fluctuation analysis against prior period and against budget, profitability, liquidity, solvency and efficiency ratios, benchmarking, and the non-GAAP measures presented alongside them. Use this to interpret results, review a counterparty's or…
events-and-field-marketing
Plans and runs events that produce pipeline — conferences, trade shows, webinars, field programs, and measuring whether any of it worked. Use this to decide whether to sponsor an event, plan a conference presence or webinar, design a field program, or work out why event spend is not producing pipeline.