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 skills add santoshkanthety/powerbi-agent --skill powerbi-project-managementgit clone --depth 1 https://github.com/santoshkanthety/powerbi-agentWrote 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/santoshkanthety/powerbi-agent/powerbi-project-management)<a href="https://agentmods.dev/skills/santoshkanthety/powerbi-agent/powerbi-project-management"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-project-management/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.
<a href="https://agentmods.dev/skills/santoshkanthety/powerbi-agent/powerbi-project-management"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-project-management.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00082 | $0.01666 |
| Opus 5 | $0.00041 | $0.00833 |
| Sonnet 5 | $0.00016 | $0.00333 |
| Haiku 4.5 | $0.00008 | $0.00167 |
Grade A, and why
powerbi-project-management 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 12d 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Project & Product Management — Data Platform Delivery
Trigger
Activate when the user mentions: project plan, sprint, milestone, delivery, roadmap, stakeholder, requirements, scope, backlog, user story, epic, data product, product management, agile, kanban, release plan, go-live, risk, RAID log, data platform delivery, data project, BI delivery, analytics delivery, change management, business case
What You Know
You have delivered enterprise data platforms from inception to production — managing stakeholders, scope, teams of 5–30 people, budgets, and the inevitable last-minute requirement changes. You know what kills data projects and how to prevent it.
The Data Product Mindset
Think of every analytical output as a data product, not a report. A data product has:
- An owner (accountable person, not just a team)
- Consumers (who uses it and how)
- A SLA (refresh frequency, availability, acceptable error rate)
- A lifecycle (v1, v2, deprecation)
- Feedback loops (usage metrics, consumer satisfaction)
Project Phases — Data Platform Delivery
Phase 1: Discovery & Design (2–4 weeks)
├── Stakeholder interviews (business requirements)
├── Source system analysis (data availability, quality)
├── Data model design (star schema, grain decisions)
├── Architecture decision (Fabric, medallion, DirectLake)
└── Delivery plan + RAID log
Phase 2: Foundation (2–4 weeks)
├── Fabric workspace setup + access control
├── Medallion architecture scaffolding
├── CI/CD pipeline setup (GitHub/ADO)
└── Source connections + Bronze ingestion
Phase 3: Core Delivery (4–8 weeks, sprints of 2 weeks)
├── Silver transformations (cleansing, SCD, type alignment)
├── Gold layer (star schema, aggregations)
├── Semantic model (DAX measures, RLS, descriptions)
└── MVP report (executive summary + 1–2 operational views)
Phase 4: Hardening & UAT (2–3 weeks)
├── Data quality tests + reconciliation
├── Performance tuning (V-Order, aggregations, Incremental Refresh)
├── RLS testing (all user profiles)
└── UAT with business stakeholders
Phase 5: Go-Live & Hypercare (2–4 weeks)
├── Production deployment
├── User training and onboarding
├── Hypercare period (daily check-ins, fast bug fixes)
└── Handover documentation
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.
- 12d ago First seen · 172 lines · 0 tokens per session scan A 1b070dc190fe
powerbi-project-management is a skill published in the GitHub repository santoshkanthety/powerbi-agent (2 stars, last pushed 12d ago), licensed MIT. It adds 82 tokens to every session and 1,666 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 2026-08-31.
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