Agent skill

Algo Social Influence

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

Measure social media influence using engagement-weighted metrics beyond follower count.

MITAuto-check passedMarketing & SEO

Install Algo Social Influence

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

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

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

At a glance

Measure social media influence using engagement-weighted metrics beyond follower count.

  • Works in 4 steps: Input Validation → Core Algorithm → Verification → …
  • The user needs to evaluate influencer effectiveness
  • 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 Influence is an agent skill from asgard-ai-platform/skills. Measure social media influence using engagement-weighted metrics beyond follower count. Use this skill when the user needs to evaluate influencer effectiveness, compare influence across accounts, or build an influence scoring system — even if they say 'who is more influential', 'influencer ranking', or 'measure social impact'.

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/authenticity-detection.md` and `references/influencer-roi.md`).

It sits in Marketing & SEO, covering Influencer and creator marketing. 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 evaluate influencer effectiveness
  • Compare influence across accounts
  • Build an influence scoring system — even if they say who is more influential
  • Influencer ranking

Example prompts

  • “who is more influential”
  • “influencer ranking”
  • “measure social impact”
  • “/algo-social-influence”

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 Influence loads about 1k tokens when it runs, and up to ~5.9k if it reads all its reference files. Until then it costs about 88 tokens; SKILL.md has 368 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~88
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
~5.9k

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). 368 words, ~1,025 tokens.

Download SKILL.mdSave it as .claude/skills/algo-social-influence/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
algo-social-influence
description
Measure social media influence using engagement-weighted metrics beyond follower count. Use this skill when the user needs to evaluate influencer effectiveness, compare influence across accounts, or build an influence scoring system — even if they say 'who is more influential', 'influencer ranking', or 'measure social impact'.
metadata.category
WP-38 社群演算法
metadata.tags
social-media, influence, influencer-marketing, metrics

Social Influence Measurement

Overview

Influence scoring evaluates an account's ability to drive actions (engagement, sharing, conversions) beyond mere reach. Combines reach, resonance (engagement depth), and relevance (topical authority). Computes as weighted composite score.

When to Use

Trigger conditions:

  • Evaluating and comparing influencers for marketing campaigns
  • Building an influence scoring or ranking system
  • Assessing brand ambassador effectiveness

When NOT to use:

  • When measuring content virality dynamics (use viral spread models)
  • When computing basic engagement rates (use engagement rate calculator)

Algorithm

IRON LAW: Follower Count ≠ Influence
Influence requires ENGAGEMENT. An account with 1M followers and
0.01% engagement rate has less influence than one with 10K followers
and 5% engagement. Measure: reach × engagement rate × relevance.
Phase 1: Input Validation

Collect per account: follower count, avg likes/comments/shares per post, posting frequency, audience demographics, topic categories. Gate: Minimum 20 recent posts for stable metrics.

Phase 2: Core Algorithm
  1. Reach score: Normalize follower count to log scale (diminishing returns)
  2. Engagement score: (avg engagements / followers) × 100, weighted by type (share > comment > like)
  3. Relevance score: Topic overlap between influencer content and target campaign
  4. Composite: Influence = w₁×Reach + w₂×Engagement + w₃×Relevance (weights tuned per campaign goal)
  5. Adjust for: audience authenticity (bot follower %), post frequency consistency
Phase 3: Verification

Spot-check: do high-scoring accounts actually drive actions? Cross-reference with historical campaign performance data if available. Gate: Top-ranked accounts have demonstrable engagement history.

Phase 4: Output

Return ranked influence scores with component breakdown.

Output Format

json
{
  "rankings": [{"account": "@handle", "influence_score": 82, "reach": 75, "engagement": 90, "relevance": 85}],
  "metadata": {"accounts_analyzed": 50, "weights": {"reach": 0.2, "engagement": 0.5, "relevance": 0.3}}
}

Examples

Sample I/O

Input: Account A: 500K followers, 0.5% engagement. Account B: 50K followers, 4.2% engagement. Same relevance. Expected: B scores higher due to engagement dominance in weighting.

Show full SKILL.md (137 more words)Show less
Edge Cases
InputExpectedWhy
Viral one-hit accountHigh recent engagement, low stabilityNeed temporal consistency check
Celebrity with low engagementHigh reach, low influence per dollarReach-only strategy, expensive
Micro-influencer nicheHigh relevance + engagementBest ROI for targeted campaigns

Gotchas

  • Fake engagement: Bot likes/comments inflate metrics. Use authenticity tools (HypeAuditor, etc.) to detect.
  • Platform differences: 2% engagement on Instagram is average; 2% on Twitter/X is excellent. Normalize by platform benchmarks.
  • Engagement pods: Groups of influencers artificially engaging with each other's content. Check if engagement comes from diverse sources.
  • Influence ≠ conversion: High engagement doesn't guarantee purchase intent. Track downstream metrics (link clicks, promo code usage) for campaign ROI.
  • Temporal decay: Influence changes. Quarterly reassessment is minimum; monthly is better for fast-moving categories.

References

  • For audience authenticity detection methods, see references/authenticity-detection.md
  • For influencer ROI measurement framework, see references/influencer-roi.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-influence of asgard-ai-platform/skills.

  • SKILL.md
  • examples/sample_scenario.md
  • references/authenticity-detection.md
  • references/influencer-roi.md

Open the folder on GitHubat commit 4e7f4f8

Compare with similar skills

Algo Social Influence 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 Influence compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Algo Social Influence this skillasgard-ai-platform/skills242—~1kAutomated safety check: PassMIT
Audience ResearchScrapeCreators/social-media-research-skills3.4k—~635Automated safety check: NotesMIT
Influencer Discoverytigerless-labs/influencer-discovery212—~2.5kAutomated safety check: NotesNone
Opencloneteam-attention/openclone130—~2.6kAutomated safety check: NotesMIT
Reelclaw Adsdansugc/reelclaw145—~3.9kAutomated safety check: NotesMIT
Affiliate CheckAffitor/affiliate-skills701—~808Automated safety check: NotesMIT

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Categories

Questions about Algo Social Influence

What does Algo Social Influence do?

Measure social media influence using engagement-weighted metrics beyond follower count. Algo Social Influence is an agent skill from asgard-ai-platform/skills. Measure social media influence using engagement-weighted metrics beyond follower count.

When should I use Algo Social Influence?

Algo Social Influence fits situations like: the user needs to evaluate influencer effectiveness; compare influence across accounts; build an influence scoring system — even if they say who is more influential; influencer ranking.

How do I install Algo Social Influence in Claude Code?

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

How do I install Algo Social Influence in Codex?

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

Can I use Algo Social Influence 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-influence -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-influence, .gemini/skills/algo-social-influence, .github/skills/algo-social-influence and .opencode/skills/algo-social-influence in your project.

What does Algo Social Influence need to run?

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

Does Algo Social Influence 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 Influence 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 Influence use?

Algo Social Influence 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 Influence 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 4.9k tokens, read only when the agent opens those files.

What are the alternatives to Algo Social Influence?

Skills that share tags, products or a category with Algo Social Influence: Audience Research (ScrapeCreators/social-media-research-skills, 3.4k stars), Influencer Discovery (tigerless-labs/influencer-discovery, 212 stars), Openclone (team-attention/openclone, 130 stars) and Reelclaw Ads (dansugc/reelclaw, 145 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Algo Social Influence?

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.