crm-assistant

crm-assistant is a skill for Claude Code, Codex from DjangoPeng/agentic-ai. It costs 114 tokens per session (1,186 once invoked), scanned A, original, MIT.

A workflow that turns sales-meeting transcripts or meeting documents into structured customer and sales-opportunity records for Feishu Bitable, a spreadsheet-style database.

In plain words
What is it for?
Use it to process text, JSON, cloud documents, or DOCX minutes into meeting records, customer updates, opportunity snapshots, follow-up tasks, and optional Feishu table entries.
Why use it?
It preserves customer history across meetings and avoids overwriting clear information with vague or missing updates.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is python ./scripts/crm_assistant.py ingest-docx-to-bitable \.

Good fit Use it to process text, JSON, cloud documents, or DOCX minutes into meeting records, customer updates, opportunity snapshots, follow-up tasks, and optional Feishu table entries.

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Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/DjangoPeng/agentic-ai
agentmods
npx agentmods add skills/djangopeng/agentic-ai/crm-assistant

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for crm-assistant

README.md
[![agentmods](https://agentmods.dev/badge/skills/djangopeng/agentic-ai/crm-assistant/github.svg)](https://agentmods.dev/skills/djangopeng/agentic-ai/crm-assistant)
Your own site
<a href="https://agentmods.dev/skills/djangopeng/agentic-ai/crm-assistant"><img src="https://agentmods.dev/badge/skills/djangopeng/agentic-ai/crm-assistant/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for crm-assistant

Your own site · 80×15
<a href="https://agentmods.dev/skills/djangopeng/agentic-ai/crm-assistant"><img src="https://agentmods.dev/badge/skills/djangopeng/agentic-ai/crm-assistant.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 114 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,186 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00114 $0.01186
Opus 5 $0.00057 $0.00593
Sonnet 5 $0.00023 $0.00237
Haiku 4.5 $0.00011 $0.00119

Measured 10d ago against content hash 345d5891af76, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

crm-assistant scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

CRM-Assistant/skills/crm-assistant/SKILL.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

CRM Assistant

在销售会议已经有可读文本后使用本 Skill。当前项目已经收敛为一个 Python CLI:scripts/crm_assistant.py

这个 skill 负责什么

把以下任一输入:

  • transcript.txt + context.json
  • 飞书会议原始 JSON
  • 飞书云文档导出的会议正文
  • Word / DOCX 会议纪要

转换成:

  • meeting_record.json
  • customer_profile_update.json
  • opportunity_update.json
  • follow_up_task.json
  • pre_meeting_brief.json
  • customer_table_rows.json
  • opportunity_snapshot_row.json
  • crm_packet.json
  • 在具备凭据时,进一步写回飞书多维表格

当前项目的关键业务规则

1. 固定两表模型

  • 客户信息(长期客户画像,按客户身份 upsert)
  • 商机快照(每次会议一条快照,保留推进轨迹)

2. 客户信息更新规则

对 客户信息的所有字段统一执行:

  • 如果本轮值是弱值(如 未明确 / 未知 / 待确认 / 空值),不要覆盖旧的明确值
  • 如果本轮值是新的明确判断,允许更新旧值
  • 沟通风格风险顾虑 采用合并策略:保留旧值并追加新值,去重后写回

3. 当前已知注意点

  • 项目已经支持 DOCX 直连入口与飞书多维表格同步
  • 同一客户多轮推进时,客户信息做增量更新,商机快照表持续追加
  • 同一项目不同阶段应优先沿用同一个商机ID,不要每轮都新建商机
  • 机会名称 应优先采用 客户公司 - 项目主题,不要把联系人姓名列表拼到最前面

优先命令

A. 直接处理 Word / DOCX 并写 CRM 结果

python ./scripts/crm_assistant.py ingest-docx-to-bitable \
  --docx-path ./meeting.docx \
  --output-dir ./runtime/your_case

B. 从飞书会议原始 JSON 提取并落 CRM

python ./scripts/crm_assistant.py ingest-feishu-raw-to-bitable \
  --raw-input-path ./raw.json \
  --output-dir ./runtime/your_case

C. 从飞书云文档正文落 CRM

python ./scripts/crm_assistant.py ingest-feishu-doc-to-bitable \
  --doc-markdown-path ./source_doc.md \
  --output-dir ./runtime/your_case

D. 仅做规则处理(已有 transcript + context)

python ./scripts/crm_assistant.py process-transcript \
  --transcript-path ./transcript.txt \
  --context-path ./context.json \
  --output-dir ./runtime/your_case/process

需要写回飞书时

如果当前环境具备飞书 app 凭据,可在 ingest 命令上追加同步参数,例如:

  • --sync-feishu
  • --app-token-or-url
  • --customer-table-id
  • --opportunity-table-id
  • 以及 app 凭据来源(显式参数、配置文件或环境变量)

若当前环境没有凭据:

  • 先完成 CRM 结构化产物生成
  • 再返回待写入内容,或由具备飞书工具能力的一侧执行写表

按需读取的参考资料

仅在需要时再读:

  • references/input_schemas.md
  • references/output_schemas.md
  • references/feishu-bitable-mapping.md
  • references/llm_prompt_template.md
  • references/llm_output_schema.md
  • references/openclaw_user_side_write_prompt.md
  • references/user_side_feishu_prompt.md

Read the full file on GitHub · 119 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 119 lines · 114 tokens per session scan A 345d5891af76

Subscribe to this mod's changes

crm-assistant is a skill published in the GitHub repository DjangoPeng/agentic-ai (147 stars, last pushed 2mo ago), licensed MIT. It adds 114 tokens to every session and 1,186 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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