Technical Analyst
tradermonty/claude-trading-skills
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.
Build employee turnover prediction models to identify flight risk and retention drivers.
Install Algo Hr Turnover
$ npx skills add asgard-ai-platform/skills --skill algo-hr-turnover -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install asgard-ai-platform/skills algo-hr-turnover --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-hr-turnover .claude/skills/algo-hr-turnover && 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-hr-turnover" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-hr-turnover into .claude/skills/algo-hr-turnover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-hr-turnover", 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-hr-turnoverType 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-hr-turnover -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install asgard-ai-platform/skills algo-hr-turnover --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-hr-turnover .agents/skills/algo-hr-turnover && 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-hr-turnover" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-hr-turnover into .agents/skills/algo-hr-turnover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-hr-turnover", 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-hr-turnover -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install asgard-ai-platform/skills algo-hr-turnover --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-hr-turnover .cursor/skills/algo-hr-turnover && 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-hr-turnover" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-hr-turnover into .cursor/skills/algo-hr-turnover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-hr-turnover", 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-hr-turnover--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-hr-turnover -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install asgard-ai-platform/skills algo-hr-turnover --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-hr-turnover .gemini/skills/algo-hr-turnover && 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-hr-turnover" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-hr-turnover into .gemini/skills/algo-hr-turnover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-hr-turnover", 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-hr-turnoverInstalls 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-hr-turnover -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-hr-turnover .github/skills/algo-hr-turnover && 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-hr-turnover" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-hr-turnover into .github/skills/algo-hr-turnover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-hr-turnover", 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-hr-turnover -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-hr-turnover --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-hr-turnover .opencode/skills/algo-hr-turnover && 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-hr-turnover" agent skill from https://github.com/asgard-ai-platform/skills/tree/main/algo-hr-turnover into .opencode/skills/algo-hr-turnover/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "algo-hr-turnover", 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-hr-turnover- GitHub stars
- 242
- Token cost
- ~1.1k tokens
- SKILL.md length
- 410 words
- Files
- 4 (incl. references)
- Skills in repo
- 207
- Repo updated
- First seen
- Licence
- MIT
At a glance
Build employee turnover prediction models to identify flight risk and retention drivers.
- Works in 4 steps: Input Validation → Core Algorithm → Verification → …
- The user needs to predict which employees are likely to leave
- 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 Hr Turnover is an agent skill from asgard-ai-platform/skills. Build employee turnover prediction models to identify flight risk and retention drivers. Use this skill when the user needs to predict which employees are likely to leave, identify retention risk factors, or prioritize HR interventions — even if they say 'attrition prediction', 'who is going to quit', or 'employee retention model'.
Its SKILL.md is about 1.1k 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/ethical-hr-ai.md` and `references/hr-features.md`).
It sits in Business, Finance & HR. 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 which employees are likely to leave
- Identify retention risk factors
- Prioritize HR interventions — even if they say attrition prediction
- Who is going to quit
Example prompts
- “attrition prediction”
- “who is going to quit”
- “employee retention model”
- “/algo-hr-turnover”
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
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 Hr Turnover loads about 1.1k tokens when it runs, and up to ~6.8k if it reads all its reference files. Until then it costs about 88 tokens; SKILL.md has 410 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); 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). 410 words, ~1,095 tokens.
Download SKILL.mdSave it as
.claude/skills/algo-hr-turnover/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- algo-hr-turnover
- description
- Build employee turnover prediction models to identify flight risk and retention drivers. Use this skill when the user needs to predict which employees are likely to leave, identify retention risk factors, or prioritize HR interventions — even if they say 'attrition prediction', 'who is going to quit', or 'employee retention model'.
- metadata.category
- WP-42 HR 演算法
- metadata.tags
- hr, turnover-prediction, attrition, retention
Employee Turnover Prediction
Overview
Turnover prediction uses classification models (logistic regression, random forest, XGBoost) to estimate the probability an employee will leave within a defined period (typically 6-12 months). Features include tenure, compensation, performance, promotion history, and engagement signals.
When to Use
Trigger conditions:
- Identifying employees at high risk of voluntary departure
- Quantifying which factors drive turnover for targeted interventions
- Prioritizing retention budgets toward highest-impact employees
When NOT to use:
- For involuntary termination planning (different process and ethics)
- When headcount is < 200 (insufficient data for reliable modeling)
Algorithm
IRON LAW: Turnover Models Predict RISK, Not Certainty
A predicted 80% turnover probability means "employees with similar
profiles historically left 80% of the time." It does NOT mean this
specific employee WILL leave. Never use model outputs as sole basis
for employment decisions — that creates legal and ethical liability.Phase 1: Input Validation
Collect: employee demographics, tenure, compensation (relative to market), last promotion date, performance ratings, manager change history, engagement survey scores, commute distance. Outcome: voluntary departure within N months. Gate: Minimum 200 turnover events, features available before departure date.
Phase 2: Core Algorithm
- Feature engineering: tenure buckets, comp ratio (salary/market median), time since last promotion, manager tenure, engagement trend
- Handle class imbalance: turnover rate typically 10-20%. Use SMOTE or class weights.
- Train: logistic regression (interpretable, HR-preferred) or GBDT (higher accuracy)
- Output: probability of departure + top risk factors per employee
Phase 3: Verification
Evaluate: AUC, precision-recall (at actionable thresholds). Backtest: did the model correctly flag employees who left in the past 6 months? Gate: AUC > 0.70, precision > 50% at top decile.
Phase 4: Output
Return risk scores with driver analysis.
Output Format
{
"risk_scores": [{"employee_id": "E123", "turnover_prob": 0.72, "risk_tier": "high", "top_drivers": ["low_comp_ratio", "no_promotion_3yr"]}],
"metadata": {"model": "xgboost", "auc": 0.78, "prediction_window_months": 12}
}Examples
Sample I/O
Input: Employee: 4yr tenure, comp ratio 0.85, no promotion in 3yr, engagement score declining Expected: High risk (>0.6). Top drivers: below-market compensation, stalled career progression.
Show full SKILL.md (157 more words)Show less
Edge Cases
| Input | Expected | Why |
|---|---|---|
| New hire (< 6 months) | Unreliable prediction | Insufficient behavioral data |
| Top performer, high comp | Still could leave | Non-financial factors (manager, culture) matter |
| Post-reorg period | Model drift likely | Unusual conditions distort patterns |
Gotchas
- Survivorship bias: Training data only includes people who were hired and stayed long enough to observe. Early-stage leavers may be underrepresented.
- Feature leakage: "Started job searching" or "updated LinkedIn" are strong predictors but ethically and legally problematic to use. Stick to internal HR data.
- Self-fulfilling prophecy: If managers treat "high risk" employees differently (less investment, fewer projects), the model prediction becomes self-fulfilling.
- Legal constraints: Using protected attributes (age, gender, ethnicity) directly or via proxies may violate employment law. Audit for disparate impact.
- Retention intervention timing: Identifying risk is only useful if HR acts. Build the model into a retention workflow with specific intervention triggers.
References
- For feature engineering from HR data, see
references/hr-features.md - For ethical AI in HR applications, see
references/ethical-hr-ai.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-hr-turnover of asgard-ai-platform/skills.
- SKILL.md
- examples/sample_scenario.md
- references/ethical-hr-ai.md
- references/hr-features.md
Open the folder on GitHubat commit 4e7f4f8
Compare with similar skills
Algo Hr Turnover 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 Hr Turnover this skillasgard-ai-platform/skills | 242 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Technical Analysttradermonty/claude-trading-skills | 3k | 4 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Regimejackson-video-resources/markov-hedge-fund-method | 484 | — | ~1.6k | Automated safety check: Pass | Custom licence | |
| Korean Government Grant Searchdjfksjd/ir-search | 391 | — | ~3.5k | Automated safety check: Notes | MIT | |
| Virtuals Protocol AcpVirtual-Protocol/openclaw-acp | 168 | 1 repos | ~6.4k | Automated safety check: Pass | None | |
| Building Streamlit Dashboardsiusztinpaul/designing-real-world-ai-agents-workshop | 512 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about Algo Hr Turnover
What does Algo Hr Turnover do?
Build employee turnover prediction models to identify flight risk and retention drivers. Algo Hr Turnover is an agent skill from asgard-ai-platform/skills. Build employee turnover prediction models to identify flight risk and retention drivers.
When should I use Algo Hr Turnover?
Algo Hr Turnover fits situations like: the user needs to predict which employees are likely to leave; identify retention risk factors; prioritize HR interventions — even if they say attrition prediction; who is going to quit.
How do I install Algo Hr Turnover in Claude Code?
Run `npx skills add asgard-ai-platform/skills --skill algo-hr-turnover -a claude-code`. Or copy the skill folder (algo-hr-turnover in asgard-ai-platform/skills) into .claude/skills/algo-hr-turnover in your project. Claude Code loads it when a task matches its description.
How do I install Algo Hr Turnover in Codex?
Run `npx skills add asgard-ai-platform/skills --skill algo-hr-turnover -a codex`. Or copy the skill folder (algo-hr-turnover in asgard-ai-platform/skills) into .agents/skills/algo-hr-turnover in your project. Codex loads it when a task matches its description.
Can I use Algo Hr Turnover 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-hr-turnover -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-hr-turnover, .gemini/skills/algo-hr-turnover, .github/skills/algo-hr-turnover and .opencode/skills/algo-hr-turnover in your project.
What does Algo Hr Turnover need to run?
SKILL.md names no scripts, command-line tools or credentials: Algo Hr Turnover is instructions for the agent only.
Does Algo Hr Turnover 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 Hr Turnover 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 Hr Turnover use?
Algo Hr Turnover 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 Hr Turnover use?
About 1.1k tokens (SKILL.md is roughly 4.4k 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 5.7k tokens, read only when the agent opens those files.
What are the alternatives to Algo Hr Turnover?
Skills that share tags, products or a category with Algo Hr Turnover: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Regime (jackson-video-resources/markov-hedge-fund-method, 484 stars), Korean Government Grant Search (djfksjd/ir-search, 391 stars) and Virtuals Protocol Acp (Virtual-Protocol/openclaw-acp, 168 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Algo Hr Turnover?
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.