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pipefy-process-impact

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🇺🇸

Original

English
🇨🇳

Translation

Chinese

Process impact

流程影响

Help the user find the one step in their process where an automation or an AI agent returns the most time, and show the arithmetic. One hop, one formula, one question per turn. The next hop comes after they have the first number.
Read the MCP reference or CLI reference only when the user names a pipe, and only for the reads listed there.
帮助用户找出其流程中最能通过自动化或 AI agent 节省时间的一个环节，并展示计算过程。每轮只处理一个环节、一个公式、一个问题。拿到第一个数字后，再推进到下一个环节。
仅当用户提到某个 pipe 时，才读取 MCP 参考 或 CLI 参考，并且只执行其中列出的读取操作。

When to use

使用场景

  • "Is it worth automating X?" / "Where do I start?" / "What is the ROI?" / "How much time does this give back?"
  • "Help me justify this internally."
  • The user wants more than the 
    Impact:
    line that 
    pipefy-process-design
    or 
    pipefy-process-intelligence
    already emitted.
Not for designing a process (
pipefy-process-design
), a full pipe diagnosis or implementation (
pipefy-process-intelligence
), building the step (
pipefy-building
, then the domain skill), or finding what a change breaks elsewhere.
  • “X 值得自动化吗？” / “我应该从哪里开始？” / “ROI 是多少？” / “这能节省多少时间？”
  • “帮我在内部论证这件事。”
  • 用户需要比 
    pipefy-process-design
    或 
    pipefy-process-intelligence
    已输出的 
    Impact:
    行更详细的内容。
不适用于设计流程（
pipefy-process-design
）、诊断或实施整条 pipe（
pipefy-process-intelligence
）、构建该环节（
pipefy-building
，然后使用对应的领域 skill），也不适用于查明某项变更会在其他环节造成什么破坏。

How to answer

如何回答

  1. Pick the hop. From the conversation, name the one manual, repetitive step with the best return: a move someone does by hand, a triage, a copy-paste, a chase. With several candidates, take the one with the most cases per week. Do not walk the whole process.
  2. Check coverage when a pipe is named. Run the reads in the reference: 
    get_pipe
    , 
    get_automations
    , 
    get_ai_agents
    , then 
    get_ai_agent
    for each active agent. If an active automation or agent already does the hop, say so, size that coverage, and move to the next uncovered hop, restating what the agent or rule already does there. Do not propose a second one. With no pipe in view, say coverage was not checked instead of claiming nothing covers the hop. 
    cards_count
    is what sits in a phase now, not volume or duration, and 
    get_cards
    selects no dates; when the answer needs time, use the timed card read under Measuring.
  3. Show the arithmetic, with the user's numbers or the gaps named:
text
hours returned per week ≈ minutes per case × cases per week / 60
cost avoided per week ≈ hours returned per week × hourly cost   (only if the user gave an hourly cost)
Never fill a gap yourself. Lead time and time per phase come from the timed card read, weekly volume from the user or a pipe report export (see Measuring), never from 
cards_count
or an undated sample. 4. Name the cheapest step that removes the hop. A traditional automation when the decision reads from fields ("if value > X, move"). An AI agent or AI automation only when the hop needs reading free text, documents, or a conversation. iPaaS when the work lives in another app. One sentence on which and why. Do not stack rule and AI as "do both now"; mention the AI step as optional when a rule leaves part of the hop manual. 5. End with one thing: the missing numbers in one short question, or the next step (the next hop, a measured export, or building it with the domain skill).
  1. 选择环节。 从对话中选出一个节省时间回报最高的人工、重复环节，例如人工移动、分流、复制粘贴或催办。如果有多个候选，选择每周处理案例数最多的一个。不要遍历整个流程。
  2. 当提到某个 pipe 时检查覆盖情况。 按照参考资料运行读取操作：
    get_pipe
    、
    get_automations
    、
    get_ai_agents
    ，然后对每个活动 agent 执行 
    get_ai_agent
    。如果已有活动自动化或 agent 覆盖该环节，应明确说明，估算覆盖量，然后转到下一个未覆盖环节，并重述 agent 或规则在该处已经执行的操作。不要建议再构建一个。如果当前没有 pipe 可见，应说明未检查覆盖情况，而不能断言没有任何内容覆盖该环节。
    cards_count
    表示当前位于某个 phase 中的内容，而不是处理量或耗时；
    get_cards
    不筛选日期。当答案需要时间数据时，使用“衡量”部分中的计时卡片读取。
  3. 展示计算过程，使用用户提供的数字，或明确标出缺失项：
text
hours returned per week ≈ minutes per case × cases per week / 60
cost avoided per week ≈ hours returned per week × hourly cost   (only if the user gave an hourly cost)
绝不要自行填补缺失项。交付周期和每个 phase 的耗时来自计时卡片读取；每周处理量来自用户或 pipe 报告导出（见“衡量”），绝不能来自 
cards_count
或无日期的样本。 4. 指出能够消除该环节的最省成本步骤。 如果决策依据来自字段（“如果 value > X，则移动”），使用传统自动化。只有当该环节需要阅读自由文本、文档或对话时，才使用 AI agent 或 AI automation。如果工作位于另一个应用中，则使用 iPaaS。用一句话说明选择哪一种以及原因。不要把规则和 AI 叠加成“现在两者都做”；如果规则执行后仍有一部分环节需要人工处理，可以将 AI 步骤作为可选项提及。 5. 以一件事结束： 用一个简短问题询问缺失的数字，或给出下一步（下一个环节、一次带度量的导出，或使用领域 skill 构建）。

Output

输出

In the user's language, four lines, under 150 words unless they asked for a written case:
text
Where it pays: [hop], [what covers it today, if anything]
Arithmetic: [formula with numbers or named gaps] = [hours per week, or the gap]
Step: [automation | AI agent | iPaaS], [one sentence on why this one]
Next: [one question, or one offer]
For a written case, expand each line into a short paragraph and add an "Assumptions" line. Money only with an hourly cost. Lead time only from the timed card read, an export, or a cycle the user stated.
使用用户的语言输出四行；除非用户要求书面案例，否则控制在 150 词以内：
text
最值得投入之处: [环节], [目前由什么覆盖（如有）]
计算: [包含数字或标明缺失项的公式] = [每周节省的小时数，或缺失项]
步骤: [自动化 | AI agent | iPaaS], [用一句话说明为何选择这一种]
下一步: [一个问题，或一个建议]
对于书面案例，将每一行扩展为一个简短段落，并增加一行“假设”。只有用户提供了每小时成本时才涉及金额。交付周期只能来自计时卡片读取、导出或用户陈述的周期。

Rules

规则

  • Report time returned to the team on repetitive hops. Asked how many people the change removes, answer in hours and say that decision is theirs.
  • Do not recommend deleting a pipe, cutting seats or credits, or moving work off Pipefy. A quiet pipe is a process with no trigger or a duplicate: ask which, then cover its hops. Delete only when the user asks for that pipe by name, and then move the work into the pipe that remains.
  • Rule before AI. Existing coverage is value already delivered: size it, do not replace it. Credits an active agent spends are the cost of work it already does, not a line to cut.
  • get_ai_agents
    takes the pipe 
    uuid
    from 
    get_pipe
    , not the numeric id; a numeric id returns a permission error. With the uuid and still a permission error, say agent coverage is unknown and do not call the hop manual on that basis.
  • 对于重复环节，报告可为团队节省的时间。如果用户问这项变更能减少多少人，应以小时数回答，并说明是否裁减人员由他们决定。
  • 不要建议删除 pipe、削减 seats 或 credits，也不要将工作移出 Pipefy。静默 pipe 是没有触发器或存在重复项的流程：先询问属于哪种情况，再评估其各个环节。只有当用户明确按名称要求删除某个 pipe 时才删除，并将工作迁移到保留的 pipe 中。
  • 规则优先于 AI。现有覆盖是已经交付的价值：评估其规模，不要替换它。活动 agent 消耗的 credits 是其已经执行工作的成本，不是可削减项。
  • get_ai_agents
    接收来自 
    get_pipe
    的 pipe 
    uuid
    ，而不是数字 id；传入数字 id 会返回权限错误。如果传入 uuid 后仍出现权限错误，应说明 agent 覆盖情况未知，不能据此判断该环节为人工操作。

Measuring

衡量

Lead time, age, and time per phase come from a timed card read: one 
execute_graphql
query on the pipe's cards that selects 
createdAt
, 
finished_at
, 
started_current_phase_at
, 
current_phase_age
, and 
phases_history
(
firstTimeIn
, 
lastTimeOut
, 
duration
in seconds per phase). The document is in the reference. It is a read, runs with no confirmation, and returns 25 cards per page (up to 50); say how many cards the numbers come from, and page with 
after
when the pipe has more. Lead time is 
finished_at
minus 
createdAt
on done cards; time in a phase is the 
duration
of its 
phases_history
entry.
Weekly volume for a whole pipe comes from the user or from a pipe report export (
created_at
per card), which is the better path when the pipe has more cards than a few pages. The export works on an existing report (
get_pipe_reports
); when the pipe has none, 
create_pipe_report
is a write, so ask first. Pass the date columns by 
name
from 
get_pipe_report_columns
; 
pipefy-reports
has the export and polling steps. The export ends in an XLSX link, so use it for volume, not for a number the user wants in the chat.
交付周期、卡片存续时间和每个 phase 的耗时来自一次计时卡片读取：对 pipe 的卡片执行一次 
execute_graphql
查询，选择 
createdAt
、
finished_at
、
started_current_phase_at
、
current_phase_age
和 
phases_history
（每个 phase 的 
firstTimeIn
、
lastTimeOut
、
duration
，单位为秒）。文档位于参考资料中。这是一次读取操作，无需确认即可运行，每页返回 25 张卡片（最多 50 张）；应说明这些数字来自多少张卡片，如果 pipe 中有更多卡片，则使用 
after
翻页。交付周期等于已完成卡片的 
finished_at
减去 
createdAt
；某个 phase 所用时间等于其 
phases_history
条目的 
duration
。
整条 pipe 的每周处理量来自用户或 pipe 报告导出（按每张卡片的 
created_at
）；当 pipe 的卡片超过几页时，导出是更好的方式。导出基于现有报告（
get_pipe_reports
）；如果该 pipe 没有报告，
create_pipe_report
是写操作，因此必须先询问。通过 
get_pipe_report_columns
按 
name
传递日期列；
pipefy-reports
skill 包含导出和轮询步骤。导出最终生成 XLSX 链接，因此应将其用于处理量统计，而不是用于用户希望在聊天中直接看到的数字。

Tools

工具

OperationRead-onlyPurpose
search_pipes
YesPipe id when only the name is known
get_pipe
YesPhases, 
cards_count
, and the pipe 
uuid
get_automations
YesHops an active rule already covers (
active
and 
actionEnabled
)
get_ai_agents
YesAgents on the pipe; active when 
disabledAt
is null
get_ai_agent
YesBehaviors with 
active: true
and the phase each acts on
execute_graphql
Yes, for a queryTimed card read: the dates and time per phase that 
get_cards
leaves out
get_pipe_reports
YesExisting reports to export for whole-pipe volume
get_pipe_report_columns
YesColumn 
name
values for the export
export_pipe_report
NoStart the export; changes no card
get_pipe_report_export
YesPoll until the file is ready
create_pipe_report
NoOnly when the pipe has no report and the user agreed
操作只读用途
search_pipes
是仅知道名称时查找 pipe id
get_pipe
是phase、
cards_count
和 pipe 
uuid
get_automations
是活动规则已覆盖的环节（
active
和 
actionEnabled
）
get_ai_agents
是pipe 上的 agent；当 
disabledAt
为 null 时为活动状态
get_ai_agent
是
active: true
的行为及其作用的 phase
execute_graphql
是，用于查询计时卡片读取：获取 
get_cards
未返回的日期和每个 phase 所用时间
get_pipe_reports
是可用于导出整条 pipe 处理量的现有报告
get_pipe_report_columns
是用于导出的列 
name
值
export_pipe_report
否启动导出；不会更改任何卡片
get_pipe_report_export
是轮询直至文件准备就绪
create_pipe_report
否仅在 pipe 没有报告且用户已同意时使用

See also

另请参阅

  • pipefy-process-design
    : new process architecture (emits an Impact line).
  • pipefy-process-intelligence
    : diagnose and improve a pipe (emits an Impact line).
  • pipefy-building
    : route the chosen step to a domain skill.
  • pipefy-automations
    , 
    pipefy-ai-agents
    , 
    pipefy-ipaas
    : build the step.
  • pipefy-reports
    : pipe report exports for lead time and weekly volume.
  • pipefy-process-design
    ：新的流程架构（会输出 
    Impact:
    行）。
  • pipefy-process-intelligence
    ：诊断并改进 pipe（会输出 
    Impact:
    行）。
  • pipefy-building
    ：将选定环节路由到对应的领域 skill。
  • pipefy-automations
    、
    pipefy-ai-agents
    、
    pipefy-ipaas
    ：构建该环节。
  • pipefy-reports
    ：用于交付周期和每周处理量的 pipe 报告导出。