Agent Adaptive Coordinator
ruvnet/ruflo
Agent skill for adaptive-coordinator - invoke with $agent-adaptive-coordinator
通过量化历史数据的自然波动幅度，自适应计算判定阈值。当需要从数据本身确定阈值（如波动阈值、影响度阈值等）、而非使用固定值时调用。仅适用于日/周粒度阈值确定。
Apache-2.0Auto-check passed
Install Bi Adaptive Threshold
$ npx skills add agentscope-ai/QwenPaw-Data --skill bi-adaptive-threshold -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-adaptive-threshold --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/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold .claude/skills/bi-adaptive-threshold && 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 "bi-adaptive-threshold" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold into .claude/skills/bi-adaptive-threshold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-adaptive-threshold", 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/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-thresholdType 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 agentscope-ai/QwenPaw-Data --skill bi-adaptive-threshold -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-adaptive-threshold --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .agents/skills && cp -r skills-src/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold .agents/skills/bi-adaptive-threshold && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "bi-adaptive-threshold" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold into .agents/skills/bi-adaptive-threshold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-adaptive-threshold", 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 agentscope-ai/QwenPaw-Data --skill bi-adaptive-threshold -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-adaptive-threshold --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold .cursor/skills/bi-adaptive-threshold && 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 "bi-adaptive-threshold" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold into .cursor/skills/bi-adaptive-threshold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-adaptive-threshold", 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/agentscope-ai/QwenPaw-Data.git --path packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold--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 agentscope-ai/QwenPaw-Data --skill bi-adaptive-threshold -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-adaptive-threshold --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold .gemini/skills/bi-adaptive-threshold && 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 "bi-adaptive-threshold" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold into .gemini/skills/bi-adaptive-threshold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-adaptive-threshold", 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 agentscope-ai/QwenPaw-Data bi-adaptive-thresholdInstalls 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 agentscope-ai/QwenPaw-Data --skill bi-adaptive-threshold -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .github/skills && cp -r skills-src/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold .github/skills/bi-adaptive-threshold && 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 "bi-adaptive-threshold" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold into .github/skills/bi-adaptive-threshold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-adaptive-threshold", 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 agentscope-ai/QwenPaw-Data --skill bi-adaptive-threshold -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-adaptive-threshold --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold .opencode/skills/bi-adaptive-threshold && 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 "bi-adaptive-threshold" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold into .opencode/skills/bi-adaptive-threshold/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-adaptive-threshold", 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
bi-adaptive-threshold- GitHub stars
- 127
- Token cost
- ~726 tokens
- SKILL.md length
- 135 words
- Files
- 2 (incl. scripts)
- Skills in repo
- 29
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
通过量化历史数据的自然波动幅度，自适应计算判定阈值。当需要从数据本身确定阈值（如波动阈值、影响度阈值等）、而非使用固定值时调用。仅适用于日/周粒度阈值确定。
- Works in 5 steps: 检查数据量是否充足（即：数据行数 < 最少数据行数），不足则直接返回 默认阈值 → 计算变化率序列，用 IQR 围栏法（四分位距 × IQR 倍数）剔除极端异常值 → 通过 ruptures 库检测结构性变化点，将数据划分为若干分段 → …
- Runs Python scripts from its folder; calls python
What it does
Bi Adaptive Threshold is an agent skill from agentscope-ai/QwenPaw-Data. 通过量化历史数据的自然波动幅度，自适应计算判定阈值。当需要从数据本身确定阈值（如波动阈值、影响度阈值等）、而非使用固定值时调用。仅适用于日/周粒度阈值确定。
Its SKILL.md is about 730 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/adaptive_threshold.py`).
The repository describes itself as: Agentic enterprise data analytics: governed facts (DataBridge), reusable methodology (Skill-Hub), and controllable execution (Host). The licence is Apache-2.0.
Example prompts
- “/bi-adaptive-threshold”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- 检查数据量是否充足（即：数据行数 < 最少数据行数），不足则直接返回 默认阈值
- 计算变化率序列，用 IQR 围栏法（四分位距 × IQR 倍数）剔除极端异常值
- 通过 ruptures 库检测结构性变化点，将数据划分为若干分段
- 取最后一段平稳区间
- 最终阈值 = 标准差 × 标准差倍数，并限制在 [阈值下限, 阈值上限] 范围内，避免阈值过于敏感或过于迟钝
What it can do on your machine
Read from SKILL.md and the folder at commit e0bae36. 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
Bi Adaptive Threshold loads about 726 tokens when it runs. Until then it costs about 25 tokens; SKILL.md has 135 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 agentscope-ai/QwenPaw-Data at commit e0bae36, republished under its Apache-2.0 licence (© agentscope-ai). 135 words, ~726 tokens.
Download SKILL.mdSave it as
.claude/skills/bi-adaptive-threshold/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- bi-adaptive-threshold
- description
- 通过量化历史数据的自然波动幅度，自适应计算判定阈值。当需要从数据本身确定阈值（如波动阈值、影响度阈值等）、而非使用固定值时调用。仅适用于日/周粒度阈值确定。
bi-adaptive-threshold
基于标准差衡量数据的自然波动幅度，从数值序列中自适应计算阈值，常见场景：
- 异常检测：确定指标波动率的异常阈值
- 影响度判定：确定事件影响度的显著性阈值
- 其他需要从数据分布中推导合理边界的场景
适用范围：仅适用于日粒度和周粒度的阈值计算。
执行步骤
1：数据准备
包含时间序列数据的 CSV 文件，至少包含以下两列：
| 列 | 说明 | 示例 |
|---|---|---|
| 日期列 | 时间标识 | 日期 |
| 数值列 | 需要计算阈值的目标数值序列 | 访问用户数 |
示例：
日期,访问用户数
2025-01-01,10000
2025-01-02,10500
2025-01-03,9800若上游步骤已产出可用数据文件则直接使用，否则自行取数。默认取近 90 天数据，若可用数据不足 90 天则取全部。
2：执行阈值计算
按以下优先级选择计算方式，命中即停：
方式一：使用脚本
路径： scripts/adaptive_threshold.py
原理：
- 检查数据量是否充足（即：数据行数 <
最少数据行数），不足则直接返回默认阈值 - 计算变化率序列，用 IQR 围栏法（四分位距 ×
IQR 倍数）剔除极端异常值 - 通过 ruptures 库检测结构性变化点，将数据划分为若干分段
- 取最后一段平稳区间：
- 若最后一段不足
最少数据行数，说明稳定数据不够，可能处于业务初期，返回默认阈值； - 计算该段数据标准差，若标准差 ≥
阈值上限，说明当前仍处于剧烈波动期，返回默认阈值
- 若最后一段不足
- 最终阈值 = 标准差 ×
标准差倍数，并限制在 [阈值下限,阈值上限] 范围内，避免阈值过于敏感或过于迟钝
若脚本适用于当前场景，按以下方式调用：
参数：
| 参数 | 说明 | 默认值 |
|---|---|---|
| --input-file | 输入数据文件路径 | （必填） |
| --date-col | 日期列名 | （必填） |
| --metric-col | 数值列名 | （必填） |
| --default-threshold | 默认阈值，按指标类型区分，详见下方说明 | （必填） |
| --min-periods | 最少数据行数 | 30 |
| --iqr-multiplier | IQR 倍数 | 1.5 |
| --std-multiplier | 标准差倍数 | 3.0 |
| --threshold-min | 阈值下限 | 0.05 |
| --threshold-max | 阈值上限 | 0.20 |
| --ruptures-method | ruptures 库的变化点检测算法（pelt/binseg/window） | pelt |
| --ruptures-penalty | ruptures 库的变化点检测的惩罚系数，值越大分段越少 | None (自动计算) |
--default-threshold是数据不足或波动剧烈时的兜底值，调用时应根据指标类型传入不同的值：
- 量值指标：默认 10%（即
--default-threshold 0.10）- 率值指标：根据率值所在区间差异化设置：
- 率值在 [40%, 60%]：±5%（即
--default-threshold 0.05）- 率值在 [20%, 40%) 或 (60%, 80%]：±3%（即
--default-threshold 0.03）- 率值在 [0%, 20%) 或 (80%, 100%]：±2%（即
--default-threshold 0.02）
调用示例：
python scripts/adaptive_threshold.py \
--input-file data.csv \
--date-col "日期" \
--metric-col "访问用户数"输出格式：
# 正常
threshold: 0.14
# 数据不足
threshold: 0.10 (数据不足，使用默认阈值)
# 波动剧烈
threshold: 0.10 (波动剧烈，使用默认阈值)方式二：自行实现
若脚本不适用于当前场景（如数据结构不匹配、场景特殊、用户有自定义需求等），基于上述核心思想自行实现阈值计算。
© agentscope-ai, Apache-2.0. 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 1 other file (scripts) in packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold of agentscope-ai/QwenPaw-Data.
- SKILL.md
- scripts/adaptive_threshold.py
Open the folder on GitHubat commit e0bae36
Compare with similar skills
Bi Adaptive Threshold 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 |
|---|---|---|---|---|---|---|
| Bi Adaptive Threshold this skillagentscope-ai/QwenPaw-Data | 127 | — | ~726 | Automated safety check: Pass | Apache-2.0 | |
| Agent Adaptive Coordinatorruvnet/ruflo | 74k | 2 repos | ~4k | Automated safety check: Pass | MIT | |
| Create Agent Adapterpaperclipai/paperclip | 99k | — | ~8k | Automated safety check: Pass | MIT | |
| Stellar Multisig Threshold Coordinatorsickn33/agentic-awesome-skills | 47k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Audit Adaptivityben-manes/caffeine | 18k | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| OpenCLI Adapter Authorjackwener/OpenCLI | 30k | 1 repos | ~3.4k | Automated safety check: Pass | Apache-2.0 |
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Questions about Bi Adaptive Threshold
What does Bi Adaptive Threshold do?
通过量化历史数据的自然波动幅度，自适应计算判定阈值。当需要从数据本身确定阈值（如波动阈值、影响度阈值等）、而非使用固定值时调用。仅适用于日/周粒度阈值确定。. Bi Adaptive Threshold is an agent skill from agentscope-ai/QwenPaw-Data.
How do I install Bi Adaptive Threshold in Claude Code?
Run `npx skills add agentscope-ai/QwenPaw-Data --skill bi-adaptive-threshold -a claude-code`. Or copy the skill folder (packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold in agentscope-ai/QwenPaw-Data) into .claude/skills/bi-adaptive-threshold in your project. Claude Code loads it when a task matches its description.
How do I install Bi Adaptive Threshold in Codex?
Run `npx skills add agentscope-ai/QwenPaw-Data --skill bi-adaptive-threshold -a codex`. Or copy the skill folder (packages/qwenpaw-data-skills/skills/atomic/bi-adaptive-threshold in agentscope-ai/QwenPaw-Data) into .agents/skills/bi-adaptive-threshold in your project. Codex loads it when a task matches its description.
Can I use Bi Adaptive Threshold 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 agentscope-ai/QwenPaw-Data --skill bi-adaptive-threshold -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bi-adaptive-threshold, .gemini/skills/bi-adaptive-threshold, .github/skills/bi-adaptive-threshold and .opencode/skills/bi-adaptive-threshold in your project.
What does Bi Adaptive Threshold need to run?
Going by SKILL.md and its folder, Bi Adaptive Threshold needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Bi Adaptive Threshold 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 Bi Adaptive Threshold 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 Bi Adaptive Threshold use?
Bi Adaptive Threshold is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Bi Adaptive Threshold use?
About 726 tokens (SKILL.md is roughly 2.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Bi Adaptive Threshold?
Skills that share tags, products or a category with Bi Adaptive Threshold: Agent Adaptive Coordinator (ruvnet/ruflo, 74k stars), Create Agent Adapter (paperclipai/paperclip, 99k stars), Stellar Multisig Threshold Coordinator (sickn33/agentic-awesome-skills, 47k stars) and Audit Adaptivity (ben-manes/caffeine, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Bi Adaptive Threshold?
agentscope-ai (a GitHub organization) maintains it in agentscope-ai/QwenPaw-Data, which has 127 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on October 5, 2026.
Source: agentscope-ai/QwenPaw-Data on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.