Data Scientist
magnus919/hermes-profiles
PhD-level expertise in data science, statistics, and machine learning.
Calculate Wilson Score confidence intervals for ranking items by positive proportion with sample size correction.
Install Algo Rank Wilson
$ npx skills add asgard-ai-platform/skills --skill algo-rank-wilson -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install asgard-ai-platform/skills algo-rank-wilson --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/algo-rank-wilson .claude/skills/algo-rank-wilson && rm -rf skills-srcUse ~/.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/
Install the "algo-rank-wilson" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-rank-wilson into .claude/skills/algo-rank-wilson/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-rank-wilson", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/asgard-ai-platform/skills/tree/main/algo-rank-wilsonType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add asgard-ai-platform/skills --skill algo-rank-wilson -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install asgard-ai-platform/skills algo-rank-wilson --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/algo-rank-wilson .agents/skills/algo-rank-wilson && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "algo-rank-wilson" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-rank-wilson into .agents/skills/algo-rank-wilson/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-rank-wilson", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgard-ai-platform/skills --skill algo-rank-wilson -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install asgard-ai-platform/skills algo-rank-wilson --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/algo-rank-wilson .cursor/skills/algo-rank-wilson && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "algo-rank-wilson" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-rank-wilson into .cursor/skills/algo-rank-wilson/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-rank-wilson", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/asgard-ai-platform/skills.git --path algo-rank-wilson--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add asgard-ai-platform/skills --skill algo-rank-wilson -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install asgard-ai-platform/skills algo-rank-wilson --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/algo-rank-wilson .gemini/skills/algo-rank-wilson && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "algo-rank-wilson" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-rank-wilson into .gemini/skills/algo-rank-wilson/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-rank-wilson", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install asgard-ai-platform/skills algo-rank-wilsonInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add asgard-ai-platform/skills --skill algo-rank-wilson -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/algo-rank-wilson .github/skills/algo-rank-wilson && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "algo-rank-wilson" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-rank-wilson into .github/skills/algo-rank-wilson/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-rank-wilson", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add asgard-ai-platform/skills --skill algo-rank-wilson -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install asgard-ai-platform/skills algo-rank-wilson --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/asgard-ai-platform/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/algo-rank-wilson .opencode/skills/algo-rank-wilson && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "algo-rank-wilson" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-rank-wilson into .opencode/skills/algo-rank-wilson/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-rank-wilson", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
algo-rank-wilson- GitHub stars
- 242
- Token cost
- ~1.1k tokens
- SKILL.md length
- 436 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 207
- Repo updated
- First seen
- Licence
- MIT
At a glance
Calculate Wilson Score confidence intervals for ranking items by positive proportion with sample size correction.
- Works in 4 steps: Input Validation → Core Algorithm → Verification → …
- The user needs to rank products by ratings
- SKILL.md covers Overview, When to Use, Algorithm and Output Format, plus 4 more sections
- Runs Python scripts from its folder; calls python
What it does
Algo Rank Wilson is an agent skill from asgard-ai-platform/skills. Calculate Wilson Score confidence intervals for ranking items by positive proportion with sample size correction. Use this skill when the user needs to rank products by ratings, sort content by approval rate, or build a 'best rated' list that accounts for sample size — even if they say 'rank by star rating', 'best rated with few reviews', or 'confidence-adjusted rating'.
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts and reference files (for example `examples/sample_input.json`, `references/bayesian-average.md` and `references/reddit-ranking.md`).
It sits in Research & Science, covering Experimental design and Statistics. 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 rank products by ratings
- Sort content by approval rate
- Build a best rated list that accounts for sample size — even if they say rank by star rating
- Best rated with few reviews
Example prompts
- “best rated”
- “rank by star rating”
- “best rated with few reviews”
- “/algo-rank-wilson”
Requirements
- Python 3
Workflow steps
4 steps, taken from the step headings in SKILL.md.
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
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
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 Rank Wilson loads about 1.1k tokens when it runs, and up to ~5k if it reads all its reference files. Until then it costs about 98 tokens; SKILL.md has 436 words of instructions outside code blocks.
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); the scripts in this folder are not scanned.
SKILL.md
The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 436 words, ~1,084 tokens.
Download SKILL.mdSave it as
.claude/skills/algo-rank-wilson/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- algo-rank-wilson
- description
- Calculate Wilson Score confidence intervals for ranking items by positive proportion with sample size correction. Use this skill when the user needs to rank products by ratings, sort content by approval rate, or build a 'best rated' list that accounts for sample size — even if they say 'rank by star rating', 'best rated with few reviews', or 'confidence-adjusted rating'.
- metadata.category
- WP-44 排名演算法
- metadata.tags
- ranking, wilson-score, confidence-interval, rating
Wilson Score Ranking
Overview
Wilson Score interval provides a lower confidence bound on the true proportion of positive ratings. Unlike simple averages, it penalizes items with few ratings, preventing a 5/5 review item (1 review) from outranking a 4.8/5 item (1000 reviews). Computes in O(1) per item.
When to Use
Trigger conditions:
- Ranking items by user ratings when review counts vary widely
- Building "top rated" or "best of" lists that are fair to well-reviewed items
- Sorting binary feedback (upvote/downvote) with confidence
When NOT to use:
- For continuous scores (use Bayesian average instead)
- When comparing items with similar sample sizes (simple average suffices)
Algorithm
IRON LAW: Never Rank by Simple Average When Sample Sizes Differ
A 5.0 average from 1 review is NOT better than 4.8 from 1000 reviews.
Wilson Score lower bound accounts for sample uncertainty:
Items with few ratings get a LOWER bound, properly reflecting our
uncertainty about their true quality.Phase 1: Input Validation
Collect per item: number of positive ratings (p), total ratings (n). For star ratings, convert to binary (e.g., 4-5 stars = positive). Gate: n > 0 for all items, confidence level chosen (typically 95%, z=1.96).
Phase 2: Core Algorithm
- Compute observed proportion: p̂ = positive / total
- Wilson lower bound: (p̂ + z²/2n - z × √(p̂(1-p̂)/n + z²/4n²)) / (1 + z²/n)
- Rank by Wilson lower bound descending (conservative estimate of true quality)
Phase 3: Verification
Check: items with many positive reviews rank above items with few reviews and same proportion. Items with very few reviews are appropriately penalized. Gate: Ranking intuitively correct on manual inspection.
Phase 4: Output
Return ranked items with scores and confidence intervals.
Output Format
{
"rankings": [{"item": "Product_A", "wilson_lower": 0.89, "positive": 950, "total": 1000, "proportion": 0.95}],
"metadata": {"confidence": 0.95, "z": 1.96, "items_ranked": 500}
}Examples
Sample I/O
Input: Item A: 1 positive / 1 total (100%). Item B: 950 positive / 1000 total (95%). Expected: B ranks higher. Wilson lower: A ≈ 0.05, B ≈ 0.94. The single review gives almost no confidence.
Show full SKILL.md (181 more words)Show less
Edge Cases
| Input | Expected | Why |
|---|---|---|
| 0 reviews | Cannot rank | n=0, undefined. Exclude or assign minimum |
| 0 positive, 100 total | Very low score | Genuinely bad item, high confidence |
| 1M positive, 1M total | Lower bound ≈ 1.0 | Massive sample, high confidence in 100% |
Gotchas
- Binary conversion: For 5-star ratings, the positive/negative threshold matters. 4+ stars as positive? 3+ stars? Different thresholds produce different rankings.
- Not for continuous data: Wilson Score is for proportions (binary outcomes). For continuous ratings, use Bayesian average with a prior.
- Cold start: New items with zero reviews can't be ranked. Use a minimum review threshold or Bayesian smoothing.
- Confidence level choice: Higher confidence (99%) penalizes small samples more aggressively. 95% is standard but tune for your use case.
- Sorting by lower bound is conservative: This approach favors well-known items. For discovery/exploration, consider also boosting items with high upper bounds (potential hidden gems).
Scripts
| Script | Description | Usage |
|---|---|---|
scripts/wilson_score.py | Compute Wilson score interval and rank items | python scripts/wilson_score.py --help |
Run python scripts/wilson_score.py --verify to execute built-in sanity tests.
References
- For Bayesian average alternative, see
references/bayesian-average.md - For Reddit's ranking algorithm (Wilson-based), see
references/reddit-ranking.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 4 other files (scripts, references) in algo-rank-wilson of asgard-ai-platform/skills.
- SKILL.md
- examples/sample_input.json
- references/bayesian-average.md
- references/reddit-ranking.md
- scripts/wilson_score.py
Open the folder on GitHubat commit 4e7f4f8
Compare with similar skills
Algo Rank Wilson 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Algo Rank Wilson this skillasgard-ai-platform/skills | 242 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Data Scientistmagnus919/hermes-profiles | 289 | — | ~3.3k | Automated safety check: Pass | MIT | |
| Data Scientistmagnus919/agent-skills | 119 | — | ~4.1k | Automated safety check: Pass | MIT | |
| Statistical PowerK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~4.4k | Automated safety check: Notes | MIT | |
| Analyze StatsAperivue/medsci-skills | 333 | — | ~7k | Automated safety check: Pass | MIT | |
| Hypothesis Testing Guidewentorai/research-plugins | 298 | 1 repos | ~2k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Algo Rank Wilson
What does Algo Rank Wilson do?
Calculate Wilson Score confidence intervals for ranking items by positive proportion with sample size correction. Algo Rank Wilson is an agent skill from asgard-ai-platform/skills. Calculate Wilson Score confidence intervals for ranking items by positive proportion with sample size correction.
When should I use Algo Rank Wilson?
Algo Rank Wilson fits situations like: the user needs to rank products by ratings; sort content by approval rate; build a best rated list that accounts for sample size — even if they say rank by star rating; best rated with few reviews.
How do I install Algo Rank Wilson in Claude Code?
Run `npx skills add asgard-ai-platform/skills --skill algo-rank-wilson -a claude-code`. Or copy the skill folder (algo-rank-wilson in asgard-ai-platform/skills) into .claude/skills/algo-rank-wilson in your project. Claude Code loads it when a task matches its description.
How do I install Algo Rank Wilson in Codex?
Run `npx skills add asgard-ai-platform/skills --skill algo-rank-wilson -a codex`. Or copy the skill folder (algo-rank-wilson in asgard-ai-platform/skills) into .agents/skills/algo-rank-wilson in your project. Codex loads it when a task matches its description.
Can I use Algo Rank Wilson 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-rank-wilson -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-rank-wilson, .gemini/skills/algo-rank-wilson, .github/skills/algo-rank-wilson and .opencode/skills/algo-rank-wilson in your project.
What does Algo Rank Wilson need to run?
Going by SKILL.md and its folder, Algo Rank Wilson needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Algo Rank Wilson 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 Rank Wilson 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Algo Rank Wilson use?
Algo Rank Wilson 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 Rank Wilson use?
About 1.1k tokens (SKILL.md is roughly 4.3k 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 3.9k tokens, read only when the agent opens those files.
What are the alternatives to Algo Rank Wilson?
Skills that share tags, products or a category with Algo Rank Wilson: Data Scientist (magnus919/hermes-profiles, 289 stars), Data Scientist (magnus919/agent-skills, 119 stars), Statistical Power (K-Dense-AI/scientific-agent-skills, 48k stars) and Analyze Stats (Aperivue/medsci-skills, 333 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Algo Rank Wilson?
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.