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Agent skill

Algo Social Virality

by asgard-ai-platform in asgard-ai-platform/skills

Model viral spread dynamics using SIR/SIS/SEIR compartmental models.

MITAuto-check passed

Install Algo Social Virality

skills CLI
$ npx skills add asgard-ai-platform/skills --skill algo-social-virality -a claude-code

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

GitHub CLI
$ gh skill install asgard-ai-platform/skills algo-social-virality --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/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/algo-social-virality .claude/skills/algo-social-virality && 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
algo-social-virality
GitHub stars
242
Token cost
~1k tokens
SKILL.md length
397 words
Files
4 (incl. references)
Skills in repo
207
Repo updated
First seen
Licence
MIT

At a glance

Model viral spread dynamics using SIR/SIS/SEIR compartmental models.

  • Works in 4 steps: Input Validation → Core Algorithm → Verification → …
  • The user needs to predict content spread patterns
  • SKILL.md covers Overview, When to Use, Algorithm and Output Format, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Algo Social Virality is an agent skill from asgard-ai-platform/skills. Model viral spread dynamics using SIR/SIS/SEIR compartmental models. Use this skill when the user needs to predict content spread patterns, estimate viral thresholds, or model information cascades in social networks — even if they say 'will this go viral', 'epidemic model for content', or 'spread prediction'.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `examples/sample_scenario.md`, `references/network-sir.md` and `references/parameter-fitting.md`).

The repository describes itself as: 301 open-source coding agent skills across 22 domains — methodology, judgment & gotchas packaged as Claude Agent Skills for the Asgard AI Platform. The licence is MIT.

When your agent uses it

  • The user needs to predict content spread patterns
  • Estimate viral thresholds
  • Model information cascades in social networks — even if they say will this go viral
  • Epidemic model for content

Example prompts

  • “will this go viral”
  • “epidemic model for content”
  • “spread prediction”
  • “/algo-social-virality”

Workflow steps

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

  1. Input Validation
  2. Core Algorithm
  3. Verification
  4. Output

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. 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 json).

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

  • Network

    No URLs in SKILL.md.

    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.

Context cost

Algo Social Virality loads about 1k tokens when it runs, and up to ~5.4k if it reads all its reference files. Until then it costs about 83 tokens; SKILL.md has 397 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~83
When it runs · the whole SKILL.md, loaded when a task matches
~1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.4k

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 asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 397 words, ~1,019 tokens.

Download SKILL.mdSave it as .claude/skills/algo-social-virality/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
algo-social-virality
description
Model viral spread dynamics using SIR/SIS/SEIR compartmental models. Use this skill when the user needs to predict content spread patterns, estimate viral thresholds, or model information cascades in social networks — even if they say 'will this go viral', 'epidemic model for content', or 'spread prediction'.
metadata.category
WP-38 社群演算法
metadata.tags
social-media, virality, epidemic-model, sir

Viral Spread Models

Overview

Compartmental models (SIR, SIS, SEIR) model how content/information spreads through populations. Susceptible → Infected → Recovered mirrors unaware → sharing → stopped sharing. Key metric: R0 (basic reproduction number). Solves as ODEs in O(T × N) for T timesteps, N compartments.

When to Use

Trigger conditions:

  • Modeling how content spreads through a social network
  • Estimating whether a campaign will achieve viral threshold
  • Analyzing post-hoc spread dynamics of viral events

When NOT to use:

  • When predicting individual user behavior (use influence scoring)
  • When measuring engagement metrics (use engagement rate calculator)

Algorithm

IRON LAW: Viral Spread Occurs ONLY When R0 > 1
R0 = transmission rate (β) / recovery rate (γ).
Below R0 = 1, content dies out regardless of initial seed size.
Above R0 = 1, exponential growth phase begins before saturation.
Design interventions (seeding, incentives) to push R0 above threshold.
Phase 1: Input Validation

Define: population size (N), initial seed size (I₀), transmission rate (β — probability of sharing upon exposure), recovery rate (γ — rate of losing interest). Gate: Parameters non-negative, β and γ estimated from historical data or assumed.

Phase 2: Core Algorithm

SIR Model: dS/dt = -βSI/N, dI/dt = βSI/N - γI, dR/dt = γI

  1. Initialize: S=N-I₀, I=I₀, R=0
  2. Iterate using Euler method or RK4 at discrete timesteps
  3. Track peak infected (maximum simultaneous sharers) and total ever-infected

SIS variant: No recovery to immune state — recovered become susceptible again (recurring content).

Phase 3: Verification

Check: S+I+R = N at all timesteps (conservation). Peak and final sizes plausible for given R0. Gate: Population conserved, dynamics consistent with R0.

Phase 4: Output

Return time series of compartments and summary metrics.

Output Format

json
{
  "time_series": [{"t": 0, "S": 9900, "I": 100, "R": 0}],
  "summary": {"R0": 2.5, "peak_infected": 3200, "peak_day": 12, "total_infected": 8500},
  "metadata": {"model": "SIR", "beta": 0.5, "gamma": 0.2, "population": 10000}
}

Examples

Sample I/O

Input: N=10000, I₀=10, β=0.3, γ=0.1 (R0=3.0) Expected: Exponential growth, peak ~4000 at day ~15, total infected ~9500

Show full SKILL.md (160 more words)Show less
Edge Cases
InputExpectedWhy
R0 = 0.8Rapid decayBelow threshold, dies out
I₀ = 1Slower start but same eventual dynamicsSingle seed takes longer to ignite
β = γ (R0=1)Linear, no growthCritical threshold, endemic equilibrium

Gotchas

  • Homogeneous mixing assumption: SIR assumes everyone interacts equally. Real networks have hubs, clusters, and weak ties. Use network-based models for realistic spread.
  • Parameter estimation: β and γ are hard to estimate for social content. Use early spread data to fit parameters, then project.
  • Content ≠ disease: Unlike diseases, content sharing is voluntary and influenced by content quality, platform algorithms, and trends. Models give rough dynamics, not precise predictions.
  • Platform algorithms: Social media algorithms amplify or suppress content. The "transmission rate" is partly determined by the platform, not just user behavior.
  • Temporal dynamics: Content virality often has a much shorter lifecycle than disease (hours-days vs weeks-months). Adjust timescales accordingly.

References

  • For network-based epidemic models, see references/network-sir.md
  • For parameter estimation from early data, see references/parameter-fitting.md

© asgard-ai-platform, 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 3 other files (references) in algo-social-virality of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_scenario.md
  • references/network-sir.md
  • references/parameter-fitting.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Algo Social Virality 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.

Algo Social Virality compared with similar skills
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Algo Social Virality this skillasgard-ai-platform/skills242—~1kAutomated safety check: PassMIT
Dynamic Workflow Modeaffaan-m/ECC277k1 repos~1.3kAutomated safety check: PassMIT
Molecular DynamicsK-Dense-AI/scientific-agent-skills48k1 repos~4.7kAutomated safety check: PassMIT
Dynamic WorkflowNousResearch/hermes-agent252k—~2.8kAutomated safety check: PassMIT
Open Dynamic Workflowssickn33/agentic-awesome-skills47k1 repos~1.1kAutomated safety check: PassMIT
Viral Generator Buildersickn33/agentic-awesome-skills47k2 repos~2kAutomated safety check: PassMIT

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Questions about Algo Social Virality

What does Algo Social Virality do?

Model viral spread dynamics using SIR/SIS/SEIR compartmental models. Algo Social Virality is an agent skill from asgard-ai-platform/skills. Model viral spread dynamics using SIR/SIS/SEIR compartmental models.

When should I use Algo Social Virality?

Algo Social Virality fits situations like: the user needs to predict content spread patterns; estimate viral thresholds; model information cascades in social networks — even if they say will this go viral; epidemic model for content.

How do I install Algo Social Virality in Claude Code?

Run `npx skills add asgard-ai-platform/skills --skill algo-social-virality -a claude-code`. Or copy the skill folder (algo-social-virality in asgard-ai-platform/skills) into .claude/skills/algo-social-virality in your project. Claude Code loads it when a task matches its description.

How do I install Algo Social Virality in Codex?

Run `npx skills add asgard-ai-platform/skills --skill algo-social-virality -a codex`. Or copy the skill folder (algo-social-virality in asgard-ai-platform/skills) into .agents/skills/algo-social-virality in your project. Codex loads it when a task matches its description.

Can I use Algo Social Virality 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 asgard-ai-platform/skills --skill algo-social-virality -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/algo-social-virality, .gemini/skills/algo-social-virality, .github/skills/algo-social-virality and .opencode/skills/algo-social-virality in your project.

What does Algo Social Virality need to run?

SKILL.md names no scripts, command-line tools or credentials: Algo Social Virality is instructions for the agent only.

Does Algo Social Virality access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Algo Social Virality 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 Algo Social Virality use?

Algo Social Virality 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 Algo Social Virality use?

About 1k tokens (SKILL.md is roughly 4.1k 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 4.3k tokens, read only when the agent opens those files.

What are the alternatives to Algo Social Virality?

Skills that share tags, products or a category with Algo Social Virality: Dynamic Workflow Mode (affaan-m/ECC, 277k stars), Molecular Dynamics (K-Dense-AI/scientific-agent-skills, 48k stars), Dynamic Workflow (NousResearch/hermes-agent, 252k stars) and Open Dynamic Workflows (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 Algo Social Virality?

asgard-ai-platform (a GitHub organization) maintains it in asgard-ai-platform/skills, which has 242 GitHub stars. The repository holds 207 skills in this directory. The repository was last updated on June 6, 2026.

Source: asgard-ai-platform/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.