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-skills/dv-securitynpx skills add microsoft/Dataverse-skills --skill dv-securitygit clone --depth 1 https://github.com/microsoft/Dataverse-skillsWhat 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 | $0.00050 | $0.01986 |
| Opus 5 | $0.00025 | $0.00993 |
| Sonnet 5 | $0.00010 | $0.00397 |
| Haiku 4.5 | $0.00005 | $0.00199 |
Grade A, and why
dv-security 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 3d 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 — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Security — Role Assignment and Self-Elevation
This skill uses first-party CLIs — PAC CLI for role changes, Dataverse CLI to verify. Do NOT write Python scripts for role operations.
Preview Before Running
Role grants and self-elevate are destructive (they change security posture and are logged to Purview). Before running, preview the action in plain prose — target user, role, environment(s) — using placeholders (<ENV_URL>, <USER_EMAIL>) for anything unknown, and ask for confirmation and missing values in the same turn. Skip the raw pac admin block; the user shouldn't have to read CLI syntax to approve a security change.
Key principle: the user should be able to evaluate what's about to happen from your first response. A bare "which environment?" fails that test; a one-line prose preview passes it.
Examples
Assign role (user given, env missing):
- ❌ "Which environment should I target?"
- ✅ "I'll assign System Administrator to
[email protected]on<ENV_URL>. Confirm to proceed and provide the target environment URL (or 'all' to list and batch)."
Admin access across all environments:
- ❌ "Please provide your email address."
- ✅ "I'll list your environments, then assign System Administrator in parallel on each one for
<YOUR_UPN>. Ifassign-userfails on any environment, I'll fall back to self-elevate (logged to Purview) for that one. Confirm to proceed and provide your UPN."
Skill boundaries
| Need | Use instead |
|---|---|
| Create or modify tables, columns, relationships | dv-metadata |
| Manage org settings, audit, bulk delete, retention | dv-admin |
| Query or read records | dv-query |
| Write, update, or delete records | dv-data |
| Tenant-level governance (DLP, env lifecycle) | pac admin --help |
Prerequisites
- PAC CLI installed and authenticated (
pac auth create) - System Administrator role in target environment (or Global/PP/D365 Admin for self-elevate)
- Active auth profile:
pac auth list - Headless / restricted-egress hosts: SDK handles role / user / business-unit ops; service principal for PAC-only ops; verify egress with
python scripts/auth.py --check. Seedv-connect/references/headless-hosts.md.
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.
- 3d ago First seen · 150 lines · 50 tokens per session scan A f40e1d1e9429
dv-security is a skill published in the GitHub repository microsoft/Dataverse-skills (213 stars, last pushed 3d ago), licensed MIT. It adds 50 tokens to every session and 1,986 once invoked, about $0.0003 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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