Dataverse Business Skills is a collection of natural-language instructions that teach AI agents how to follow business processes, policies, and domain knowledge for Microsoft Dataverse. Organizations use the skills with Dataverse environments connected to products such as Power Apps, Dynamics 365, or Power Platform. The catalogue entries are skills from this collection.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/microsoft/dataverse-business-skills/log-call-transcriptsnpx skills add microsoft/dataverse-business-skills --skill log-call-transcriptsgit clone --depth 1 https://github.com/microsoft/dataverse-business-skillsWrote 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.
[](https://agentmods.dev/skills/microsoft/dataverse-business-skills/log-call-transcripts)<a href="https://agentmods.dev/skills/microsoft/dataverse-business-skills/log-call-transcripts"><img src="https://agentmods.dev/badge/skills/microsoft/dataverse-business-skills/log-call-transcripts.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00076 | $0.02781 |
| Opus 5 | $0.00038 | $0.01391 |
| Sonnet 5 | $0.00015 | $0.00556 |
| Haiku 4.5 | $0.00008 | $0.00278 |
Grade A, and why
log-call-transcripts 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 6d 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.
How it starts
The opening of the file, as written. The whole thing — 294 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Log Call Transcripts
When a sales representative uploads or provides a call transcript, this skill extracts actionable information from the conversation and creates a properly structured Phone Call activity record in Dataverse. This eliminates manual data entry and ensures consistent activity logging across the sales team.
Instructions
Step 1: Receive and Parse Transcript
When the user provides a call transcript:
- Accept the transcript content (text or file upload)
- Identify the transcript format and parse it appropriately
- Extract speaker labels if available (e.g., "Sales Rep:", "Customer:")
Step 2: Extract Key Information from Transcript
Analyze the transcript to identify and extract:
Participant Information:
- Customer name(s) mentioned
- Company/Account name mentioned
- Customer's role or title if mentioned
- Phone numbers discussed
Call Metadata:
- Call duration (if mentioned or calculable)
- Date/time of call (if mentioned, otherwise use current datetime)
- Call direction (inbound/outbound based on context)
Content Analysis:
- Subject/Topic: Main purpose of the call (e.g., "Product demo follow-up", "Pricing discussion", "Support inquiry")
- Key Discussion Points: Summarize 3-5 main topics discussed
- Action Items: Any commitments or next steps mentioned
- Customer Pain Points: Problems or challenges the customer mentioned
- Competitor Mentions: Any competitor products or companies referenced
- Budget Signals: Any pricing or budget discussions
- Decision Maker Signals: References to decision-making process or stakeholders
- Timeline Signals: Any urgency or timing requirements mentioned
Step 3: Match to Existing Records
Query Dataverse to find matching records:
Find Account:
Use read_query to search the account table:
- Search by company name mentioned in transcript
- Match on account.name field
- If multiple matches, list them for user confirmation
Find Contact:
Use read_query to search the contact table:
- Search by participant name(s) from transcript
- Match on contact.fullname or contact.firstname + contact.lastname
- Filter by accountid if account was identified
- If multiple matches, list them for user confirmation
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.
- 6d ago First seen · 294 lines · 76 tokens per session scan A d5f4398370f4
log-call-transcripts is a skill published in the GitHub repository microsoft/dataverse-business-skills (49 stars, last pushed 5mo ago), licensed MIT. It adds 76 tokens to every session and 2,781 once invoked, about $0.0004 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.
Other skills, from other repositories
orbit-notion
Open Orbit briefing skill — selected by the Orbit pipeline when Notion is the user's only connected connector, or when the user explicitly scopes their daily digest to Notion. Pulls the past 24 hours of document edits, comments, mentions, and database row changes from the user's authenticated Notion connection and…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
feishu
Work with Feishu or Lark bots, docs, sheets, bitables, approval flows, and OpenAPI/MCP setup without hardcoding credentials.
pinchtab-mcp
Use this skill when a task requires browser automation through PinchTab's MCP server connected to a remote browser instance. Covers navigation, element interaction, data extraction, form filling, multi-step flows, and session management via MCP tools.
peekaboo
Capture and automate macOS UI with the Peekaboo CLI.
mochi-remind
Handle due reminders — notify the user with natural language and mark them done.