Attribution
Nexus-JPF/note-companion
When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools.
计算各维度（组）值对指标变动的贡献度，支持可加型量值指标和加权平均型/率值指标。当需要计算贡献度、解释指标"为什么涨/跌"时调用。
Apache-2.0Auto-check passed
Install Bi Attribution Analysis
$ npx skills add agentscope-ai/QwenPaw-Data --skill bi-attribution-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-attribution-analysis --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-attribution-analysis .claude/skills/bi-attribution-analysis && 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-attribution-analysis" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-attribution-analysis into .claude/skills/bi-attribution-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-attribution-analysis", 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-attribution-analysisType 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-attribution-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-attribution-analysis --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-attribution-analysis .agents/skills/bi-attribution-analysis && 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-attribution-analysis" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-attribution-analysis into .agents/skills/bi-attribution-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-attribution-analysis", 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-attribution-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-attribution-analysis --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-attribution-analysis .cursor/skills/bi-attribution-analysis && 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-attribution-analysis" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-attribution-analysis into .cursor/skills/bi-attribution-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-attribution-analysis", 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-attribution-analysis--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-attribution-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-attribution-analysis --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-attribution-analysis .gemini/skills/bi-attribution-analysis && 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-attribution-analysis" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-attribution-analysis into .gemini/skills/bi-attribution-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-attribution-analysis", 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-attribution-analysisInstalls 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-attribution-analysis -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-attribution-analysis .github/skills/bi-attribution-analysis && 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-attribution-analysis" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-attribution-analysis into .github/skills/bi-attribution-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-attribution-analysis", 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-attribution-analysis -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-attribution-analysis --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-attribution-analysis .opencode/skills/bi-attribution-analysis && 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-attribution-analysis" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-attribution-analysis into .opencode/skills/bi-attribution-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-attribution-analysis", 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-attribution-analysis- GitHub stars
- 124
- Token cost
- ~1.2k tokens
- SKILL.md length
- 105 words
- Files
- 2 (incl. scripts)
- Skills in repo
- 29
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
计算各维度（组）值对指标变动的贡献度，支持可加型量值指标和加权平均型/率值指标。当需要计算贡献度、解释指标"为什么涨/跌"时调用。
- Runs Python scripts from its folder; calls python
What it does
Bi Attribution Analysis is an agent skill from agentscope-ai/QwenPaw-Data. 计算各维度（组）值对指标变动的贡献度，支持可加型量值指标和加权平均型/率值指标。当需要计算贡献度、解释指标"为什么涨/跌"时调用。
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/contribution_calc.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
- “为什么涨/跌”
- “/bi-attribution-analysis”
Requirements
- Python 3
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 Attribution Analysis loads about 1.2k tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 105 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). 105 words, ~1,246 tokens.
Download SKILL.mdSave it as
.claude/skills/bi-attribution-analysis/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- bi-attribution-analysis
- description
- 计算各维度（组）值对指标变动的贡献度，支持可加型量值指标和加权平均型/率值指标。当需要计算贡献度、解释指标"为什么涨/跌"时调用。
bi-attribution-analysis
计算各维度（组）值对指标变动的贡献度，量化每个维度值对整体变动的贡献大小，常见场景：
- 维度下拆归因：指标异常后，逐维度下拆定位驱动变化的关键因素
- 交叉维度归因：多维度组合下拆，定位高贡献的维度组合
适用指标：
- 维度间可加的量值指标：各维度值可直接求和得到整体值，如访问用户数、GMV、订单量
- 率值指标：整体值 = 分子总和 / 分母总和，如转化率、留存率
- 加权平均型指标：整体值由各维度值按权重加权得到。如按渠道拆解客单价（= 各渠道总收入 / 各渠道订单数，各渠道客单价不可直接求和）、按客户群拆解人均收入（= 各群总收入 / 各群用户数）
执行步骤
1：数据准备
包含维度往期/当期指标数据的 CSV 文件，至少包含以下列：
维度间可加的量值指标：
| 列 | 说明 | 示例 |
|---|---|---|
| 维度列 | 维度名称 | 渠道 |
| 往期值列 | 往期指标值 | 销售额_往期 |
| 当期值列 | 当期指标值 | 销售额_当期 |
率值指标额外需包含分子和分母的往期/当期值：
| 列 | 说明 | 示例 |
|---|---|---|
| 分子_往期 | 往期分子值 | 转化人数_往期 |
| 分子_当期 | 当期分子值 | 转化人数_当期 |
| 分母_往期 | 往期分母值 | 访问人数_往期 |
| 分母_当期 | 当期分母值 | 访问人数_当期 |
加权平均型指标额外需包含指标的分子（被加权的总量）和分母（权重来源）的往期/当期值，示例同上。
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。
2：选择贡献度计算方法
根据指标类型选择计算方法：
维度间可加的量值指标：
| 方法 | 适用场景 |
|---|---|
| quantity-standard（标准法） | 默认选择。按维度增量占总增量的比例计算贡献度 |
| quantity-separate（正负分离法） | 当正负变化相互抵消严重时使用（例如，某方向变动量超过整体变动的 30%），将正贡献和负贡献分别归一化，避免抵消掩盖真实驱动因素 |
加权平均型指标和率值指标：
| 方法 | 适用场景 |
|---|---|
| ratio-cross-term（保留交叉项法） | 默认选择。将变动拆解为三部分：结构效应（权重变化的影响）、水平效应（指标值本身变化的影响）和交互效应（两者同时变化产生的交叉影响） |
| ratio-average（平均权重法） | 当不需要区分交互效应、希望结果更简洁时使用。用往期和当期的平均权重消除交互项，只输出结构效应和水平效应两项 |
3：执行贡献度计算
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/contribution_calc.py
原理：按上述方法计算各维度值的贡献度。支持传入多个维度列进行交叉分析。
若脚本适用于当前场景，按以下方式调用：
参数：
| 参数 | 说明 |
|---|---|
| --input-file | 输入数据文件路径（必填） |
| --dimension | 维度列名，支持多个（必填，如 --dimension 渠道 端类型） |
| --history-col | 往期值列名（必填） |
| --current-col | 当期值列名（必填） |
| --method | 归因方法（必填，见上方方法选择表） |
| --numerator-history | 分子往期列名（率值/加权平均指标时必填） |
| --numerator-current | 分子当期列名（率值/加权平均指标时必填） |
| --denominator-history | 分母往期列名（率值/加权平均指标时必填） |
| --denominator-current | 分母当期列名（率值/加权平均指标时必填） |
| --output-file | 输出结果文件路径（可选） |
调用示例：
# 单维度 - 量值指标标准法
python scripts/contribution_calc.py \
--input-file data.csv \
--dimension "渠道" \
--history-col "销售额_往期" \
--current-col "销售额_当期" \
--method quantity-standard \
--output-file contribution_result.csv
# 多维度交叉 - 量值指标标准法
python scripts/contribution_calc.py \
--input-file data.csv \
--dimension "渠道" "端类型" \
--history-col "销售额_往期" \
--current-col "销售额_当期" \
--method quantity-standard \
--output-file contribution_result.csv
# 率值指标 - 保留交叉项法
python scripts/contribution_calc.py \
--input-file data.csv \
--dimension "品类" \
--history-col "转化率_往期" \
--current-col "转化率_当期" \
--numerator-history "转化人数_往期" \
--numerator-current "转化人数_当期" \
--denominator-history "访问人数_往期" \
--denominator-current "访问人数_当期" \
--method ratio-cross-term \
--output-file contribution_result.csv
# 加权平均指标 - 按渠道拆客单价
python scripts/contribution_calc.py \
--input-file data.csv \
--dimension "渠道" \
--history-col "客单价_往期" \
--current-col "客单价_当期" \
--numerator-history "总收入_往期" \
--numerator-current "总收入_当期" \
--denominator-history "订单数_往期" \
--denominator-current "订单数_当期" \
--method ratio-cross-term \
--output-file contribution_result.csv输出格式：
quantity-standard（标准法）：
渠道 往期值 当期值 增量 贡献度
华东 100 150 +50 83.3%
华南 80 100 +20 33.3%
华北 60 50 -10 -16.7%ratio-cross-term（保留交叉项法）：
品类 往期率值 当期率值 权重_往期 权重_当期 结构效应 水平效应 交互效应 总贡献
A类 5.00pt 6.00pt 60.00% 55.00% -0.25pt +0.55pt -0.05pt +0.25pt
B类 3.00pt 4.00pt 40.00% 45.00% +0.15pt +0.45pt +0.05pt +0.65pt方式二：自行实现
若脚本不适用于当前场景，参考上述原理自行实现贡献度计算。
© 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-attribution-analysis of agentscope-ai/QwenPaw-Data.
- SKILL.md
- scripts/contribution_calc.py
Open the folder on GitHubat commit e0bae36
Compare with similar skills
Bi Attribution Analysis 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 Attribution Analysis this skillagentscope-ai/QwenPaw-Data | 124 | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | |
| AttributionNexus-JPF/note-companion | 870 | 1 repos | ~5.2k | Automated safety check: Pass | MIT | |
| Performance AttributionHKUDS/Vibe-Trading | 35k | — | ~3.1k | Automated safety check: Pass | MIT | |
| Direction Attributethedaviddias/Front-End-Checklist | 74k | — | ~534 | Automated safety check: Pass | MIT | |
| Fetchpriority Attributethedaviddias/Front-End-Checklist | 74k | — | ~535 | Automated safety check: Pass | MIT | |
| Lang Attributethedaviddias/Front-End-Checklist | 74k | — | ~995 | Automated safety check: Pass | MIT |
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Questions about Bi Attribution Analysis
What does Bi Attribution Analysis do?
计算各维度（组）值对指标变动的贡献度，支持可加型量值指标和加权平均型/率值指标。当需要计算贡献度、解释指标"为什么涨/跌"时调用。. Bi Attribution Analysis is an agent skill from agentscope-ai/QwenPaw-Data.
How do I install Bi Attribution Analysis in Claude Code?
Run `npx skills add agentscope-ai/QwenPaw-Data --skill bi-attribution-analysis -a claude-code`. Or copy the skill folder (packages/qwenpaw-data-skills/skills/atomic/bi-attribution-analysis in agentscope-ai/QwenPaw-Data) into .claude/skills/bi-attribution-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Bi Attribution Analysis in Codex?
Run `npx skills add agentscope-ai/QwenPaw-Data --skill bi-attribution-analysis -a codex`. Or copy the skill folder (packages/qwenpaw-data-skills/skills/atomic/bi-attribution-analysis in agentscope-ai/QwenPaw-Data) into .agents/skills/bi-attribution-analysis in your project. Codex loads it when a task matches its description.
Can I use Bi Attribution Analysis 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-attribution-analysis -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-attribution-analysis, .gemini/skills/bi-attribution-analysis, .github/skills/bi-attribution-analysis and .opencode/skills/bi-attribution-analysis in your project.
What does Bi Attribution Analysis need to run?
Going by SKILL.md and its folder, Bi Attribution Analysis needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Bi Attribution Analysis 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 Attribution Analysis 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 Attribution Analysis use?
Bi Attribution Analysis 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 Attribution Analysis use?
About 1.2k tokens (SKILL.md is roughly 5k 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 Attribution Analysis?
Skills that share tags, products or a category with Bi Attribution Analysis: Attribution (Nexus-JPF/note-companion, 870 stars), Performance Attribution (HKUDS/Vibe-Trading, 35k stars), Direction Attribute (thedaviddias/Front-End-Checklist, 74k stars) and Fetchpriority Attribute (thedaviddias/Front-End-Checklist, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Bi Attribution Analysis?
agentscope-ai (a GitHub organization) maintains it in agentscope-ai/QwenPaw-Data, which has 124 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.