方法与优势
三个 Python 工具分别处理流程图、瓶颈排序和周期计算。
记录业务流程,分析瓶颈、等待时间和周期分布。
记录业务流程,分析瓶颈、等待时间和周期分布。三个 Python 工具分别处理流程图、瓶颈排序和周期计算。
三个 Python 工具分别处理流程图、瓶颈排序和周期计算。
绘制供应商入驻与审批交接流程;定位运营流程中的等待瓶颈;比较流程变更前后的处理周期。
流程步骤、负责人、交接、实测处理与等待时间,以及实例时间戳。
使用支持 Skill 且能访问文件的 Agent。随包 Python 辅助工具需要 Python 3;提供数据前先查看样例结构。
根因建议是假设。工具分析输入数据,不实时观察系统或自动改造流程。
仓库安装器会把此 Skill 的完整目录复制到 Codex skills 目录。需具备 Git 及安装器要求的 shell/Python 环境。
git clone https://github.com/alirezarezvani/claude-skills.git
cd claude-skills
git checkout 6d2f02ea077eead1bee5411a31bcc6db5a11a70c
./scripts/codex-install.sh --skill process-mapper以下为已核对版本未经改写的 SKILL.md。安装完整包才能保留引用的脚本、素材和指引。下方启动提示词为 EcomAgentTools 编写的示例。
2026 年 10 月 25 日核对源码及随包文件:GitHub 6d2f02ea077e。本次为静态审查,不代表已完成安装运行或业务效果测试。
MIT License Copyright (c) 2025 Alireza Rezvani Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
---
name: process-mapper
description: Use when a BizOps lead, COO, or process-improvement owner needs to document an end-to-end business process (procurement, employee onboarding, incident handoff, customer-onboarding, claims adjudication) in BPMN-style notation, measure cycle times by stage, surface where work spends most of its time waiting vs. being worked, and quantify the gap between processing time and total elapsed time. Pairs Lean / Six Sigma / Theory-of-Constraints canon with deterministic stdlib-only Python tools to produce a process map, a ranked bottleneck list (with severity + root-cause hypothesis), and a cycle-time analysis (P50, P90, value-add ratio, Little's-Law throughput). Distinct from sales-pipeline, system-reliability (SLO), and strategic-OKR work — this is tactical process documentation for internal operations.
license: MIT
metadata:
version: 2.8.0
author: claude-code-skills
tags: [bizops, process, bpmn, bottleneck, cycle-time, lean, six-sigma, value-stream]
compatible_tools: [claude-code, codex-cli, cursor, antigravity, opencode, gemini-cli]
---
# process-mapper
BPMN-style business process documentation, bottleneck detection, and cycle-time analysis for internal-operations leaders.
## Purpose
Internal-operations work suffers from three recurring failure modes:
1. **Implicit process** — the steps exist only in tribal knowledge, so handoffs drop and onboarding takes weeks.
2. **Invisible waiting** — most of the elapsed time on any business process is queue / wait / approval time, not actual work; teams optimize the wrong stage.
3. **Local optimization** — Goldratt's Theory of Constraints is ignored; resources are added to non-constraint stages, gaining nothing.
This skill produces a documented process map, identifies where work waits, and points the constraint out by name with deterministic logic — not LLM intuition.
## When to use
- Documenting a new business process (procurement intake, vendor onboarding, employee onboarding, incident handoff, expense reimbursement, customer onboarding, claims adjudication).
- An existing process is "too slow" but nobody can name the bottleneck.
- Cycle time is being measured but value-add ratio is not — so the team can't tell whether the process is healthy or waste-heavy.
- Cross-functional handoffs are dropping work and root cause is unclear.
## Workflow
Five-step deterministic flow:
1. **Intake.** Capture the process as a JSON file with one entry per stage: `name`, `owner`, `type` (`value-add` | `wait` | `rework`), `duration_minutes_p50`, `duration_minutes_p90`. Use `assets/process_template.md` and its JSON skeleton.
2. **Map stages.** Run `process_documenter.py` to produce an ASCII swim-lane diagram + a normalized JSON artifact. The swim-lane separates lanes by owner so cross-functional handoffs become visible.
3. **Measure cycle time.** Run `cycle_time_analyzer.py` to compute total P50, total P90, value-add ratio (VA%), and a Little's-Law throughput estimate. Verdict: VA% > 25% = HEALTHY, 10–25% = TYPICAL, < 10% = WASTE-HEAVY.
4. **Detect bottlenecks.** Run `bottleneck_detector.py` with the appropriate `--profile` (saas / services / manufacturing / healthcare). Output is a ranked list with severity (CRITICAL / HIGH / MEDIUM), root-cause hypothesis, and one recommended action per finding.
5. **Recommend.** Pair the bottleneck list with the cycle-time verdict; recommend a single constraint-focused intervention per Goldratt's "subordinate everything to the constraint" rule. Don't recommend optimization of a non-constraint stage.
## Scripts
**`scripts/process_documenter.py`** — Reads a process JSON, validates it, and emits a text-based BPMN-style swim-lane diagram in Markdown (lanes by owner, stages annotated with type + duration). Also outputs a normalized JSON artifact for downstream tools. Stdlib only. `--sample` prints a 6-stage procurement-intake example.
**`scripts/bottleneck_detector.py`** — Applies three deterministic detection rules: (a) stage P50 > 2× mean of value-add stages, (b) wait-state % > 40% of total cycle, (c) rework % > 15%. Thresholds adjust by `--profile` because SaaS, services, manufacturing, and healthcare have different "normal" wait ratios. Output is a ranked list with severity, hypothesis, action.
**`scripts/cycle_time_analyzer.py`** — Computes total P50 and P90 cycle time, value-add ratio (VA%), wait %, rework %, and a Little's-Law throughput estimate (WIP / cycle time). Per Lean canon: VA% > 25% = HEALTHY, 10–25% = TYPICAL (most non-manufacturing processes land here), < 10% = WASTE-HEAVY.
## Quick example
```bash
# Renders a BPMN-style swim-lane diagram + normalized JSON for the built-in 6-stage procurement-intake example
cd business-operations/skills/process-mapper && python3 scripts/process_documenter.py --sample
```
## References
- `references/lean_six_sigma_canon.md` — TIMWOOD wastes, value-stream mapping, Theory of Constraints, Kanban WIP, Little's Law. Cites Womack & Jones, Rother & Shook, Goldratt, Ohno, Liker, Pyzdek, Anderson.
- `references/bpmn_essentials.md` — Pools, lanes, gateways, events, message flows, common notation mistakes. Cites the OMG BPMN 2.0 spec, Silver, Allweyer, Freund/Rücker, OASIS, ISO/IEC 19510:2013.
- `references/bottleneck_anti_patterns.md` — Seven specific anti-patterns drawn from Goldratt, Kim et al., Spear, DORA, Deming, and process-mining research.
## Assumptions
1. The user can provide stage-level cycle-time data (even rough P50 / P90 estimates). If they cannot, the first step is to instrument the process — not to map it.
2. "Process" here means a repeatable business workflow with discrete stages, not a one-off project.
3. The user has authority to act on bottlenecks (or can route findings to someone who does). Without that, the output is academic.
4. Stage `type` is honest: a "value-add" stage labeled as such by the user really does change the work product from the customer's perspective. Mis-labelling waiting as value-add is the most common data-quality failure.
## Anti-patterns
- **Mapping every process at once.** Pick one. Goldratt: the constraint is a single point.
- **Optimizing the non-constraint.** If stage 4 is the bottleneck, speeding up stage 2 just builds inventory in front of stage 4. Subordinate everything to the constraint.
- **Mistaking total cycle time for processing time.** They are almost never the same; VA% reveals the gap.
- **Adding people to a wait-bound process.** Wait time is not solved by more headcount; it's solved by removing the handoff or batch.
- **Treating rework as a separate problem.** Rework loops belong in the process map. Hiding them understates true cycle time.
## Distinct from
- **business-growth skills** — external sales motion, lead-funnel conversion, customer-success retention. Process-mapper is *internal* operations.
- **engineering/slo-architect** — system-reliability SLOs / error budgets / burn-rate alerts. Process-mapper is *business-process* cycle time, not system uptime.
- **c-level-advisor (COO / CEO)** — strategic prioritization of which processes to fix. Process-mapper is the tactical instrument used after that prioritization decision.
- **project-management skills** — Jira / Confluence ticket workflow tooling. Process-mapper is process *design*, not ticket *tracking*.
## Forcing-question library (Matt Pocock grill discipline)
Before invoking the tools, the orchestrator (or `/cs-grill-bizops`) walks the user through these questions **one at a time, with a recommended answer + canon citation**. Never bundled.
1. **"Do you have measured cycle times for the top-3 longest stages, or only estimates?"**
Recommended: insist on measured data.
Canon: Goldratt 1984 (*The Goal*) — optimizing estimated bottlenecks reliably attacks the wrong constraint.
2. **"Are you mapping the *current* process (as-is) or the *intended* process (to-be)?"**
Recommended: map as-is first. To-be after bottleneck is identified.
Canon: Rother & Shook 1999 (*Learning to See*) — value-stream mapping starts with the current state, always.
3. **"Where do handoffs occur between teams, and how long does each handoff wait?"**
Recommended: log every handoff with median wait time.
Canon: Reinertsen 2009 (*Principles of Product Development Flow*) — wait time at handoffs is the largest invisible cost.
4. **"What's your batch size at each stage?"**
Recommended: drive batch size toward 1 wherever possible.
Canon: Anderson 2010 (*Kanban*) — batch size correlates 1:1 with cycle time variance.
5. **"What's the rework rate per stage?"**
Recommended: surface it explicitly; rework loops belong in the map.
Canon: Pyzdek (*Six Sigma Handbook*) — hidden rework drives 30-50% of total cycle time in service processes.
Walk depth-first. Don't open question 4 before 1-3 are answered. After all 5 are locked, invoke `process_documenter.py` → `bottleneck_detector.py` → `cycle_time_analyzer.py` in sequence.
以下是主要功能的用例提示词,可以直接复制使用。
绘制供应商入驻与审批交接流程 适用于:绘制供应商入驻与审批交接流程。请准备:流程步骤、负责人、交接、实测处理与等待时间,以及实例时间戳。
请使用已安装的 process-mapper Skill。任务:绘制供应商入驻与审批交接流程。输入:[INPUT]。限制:[CONSTRAINTS]。先检查缺失信息,再输出可审查的结果、依据、假设和下一步。根因建议是假设。工具分析输入数据,不实时观察系统或自动改造流程。[INPUT][CONSTRAINTS]定位运营流程中的等待瓶颈 适用于:定位运营流程中的等待瓶颈。请准备:流程步骤、负责人、交接、实测处理与等待时间,以及实例时间戳。
请使用已安装的 process-mapper Skill。任务:定位运营流程中的等待瓶颈。输入:[INPUT]。限制:[CONSTRAINTS]。先检查缺失信息,再输出可审查的结果、依据、假设和下一步。根因建议是假设。工具分析输入数据,不实时观察系统或自动改造流程。[INPUT][CONSTRAINTS]比较流程变更前后的处理周期 适用于:比较流程变更前后的处理周期。请准备:流程步骤、负责人、交接、实测处理与等待时间,以及实例时间戳。
请使用已安装的 process-mapper Skill。任务:比较流程变更前后的处理周期。输入:[INPUT]。限制:[CONSTRAINTS]。先检查缺失信息,再输出可审查的结果、依据、假设和下一步。根因建议是假设。工具分析输入数据,不实时观察系统或自动改造流程。[INPUT][CONSTRAINTS]根因建议是假设。工具分析输入数据,不实时观察系统或自动改造流程。
2026 年 10 月 25 日核对源码及随包文件:GitHub 6d2f02ea077e。本次为静态审查,不代表已完成安装运行或业务效果测试。
使用获授权输入,不把密钥贴入提示词。采用前检查面向客户的声明、计算、代码改动及任何拟议的外部操作。
记录业务流程,分析瓶颈、等待时间和周期分布。三个 Python 工具分别处理流程图、瓶颈排序和周期计算。
按实际 Agent 选择方式,安装完整包,不要只复制页面中的 SKILL.md。 流程步骤、负责人、交接、实测处理与等待时间,以及实例时间戳。 开启新 Agent 会话,明确要求使用 process-mapper。先用小型样本尝试下方一个场景,并检查输出。
绘制供应商入驻与审批交接流程;定位运营流程中的等待瓶颈;比较流程变更前后的处理周期
根因建议是假设。工具分析输入数据,不实时观察系统或自动改造流程。
2026 年 10 月 25 日核对源码及随包文件:GitHub 6d2f02ea077e。本次为静态审查,不代表已完成安装运行或业务效果测试。
2026 年 10 月 25 日核对源码及随包文件:GitHub 6d2f02ea077e。本次为静态审查,不代表已完成安装运行或业务效果测试。
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