microsoft/power-platform-skills is a plugin marketplace containing reusable skills, agents, and commands for developing with Microsoft Power Platform. Developers use it to build and deploy Power Pages sites, model-driven Power Apps, and related solutions through Claude Code or GitHub Copilot. The catalogue entries are the marketplace's included skills, agents, plugins, and other agent components.
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 microsoft/power-platform-skills --skill analyze-driversgit clone --depth 1 https://github.com/microsoft/power-platform-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/power-platform-skills/analyze-drivers)<a href="https://agentmods.dev/skills/microsoft/power-platform-skills/analyze-drivers"><img src="https://agentmods.dev/badge/skills/microsoft/power-platform-skills/analyze-drivers/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/microsoft/power-platform-skills/analyze-drivers"><img src="https://agentmods.dev/badge/skills/microsoft/power-platform-skills/analyze-drivers.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 | $0.00025 | $0.00745 |
| Opus 5.5 | $0.00010 | $0.00298 |
| Sonnet 5.5 | $0.00005 | $0.00149 |
| Haiku 4.5 | $0.00003 | $0.00075 |
Grade A, and why
analyze-drivers 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 9d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Drivers: association before explanation
Use the shared contract and filter/unit reference. Reuse metadata and frozen baseline scope; choose a specific defined outcome and relevant case-level attributes from the user's context, without a candidate quota. If none is known, ask; do not sweep. State a testable hypothesis, possible competing explanation and what would distinguish them. Load the investigation method for evidence/status tracking. For utilization, first check timestamp imports and the zero-duration convention in the unit reference. A cohort-mix convention is not resource efficiency or measured productive time.
Ordered trace
-
Check A's metadata level before correlation. Reuse a cached signal instead of repeating it.
get_correlation_v2 {S,attributeName:A,influenceFormula:I,sortOrder:"Descending",filterOptions:F}.Outcome I Duration / waiting / active time DurationInfluence / WaitingTimeInfluence / ActiveTimeInfluence Utilization / event count CaseUtilizationInfluence / EventCountInfluence Rework / loops / self-loops ReworkCountInfluence / LoopCountInfluence / SelfloopCountInfluence Use the advertised enum and exact spelling. There are no
itemsPerPage,itemsToSkip,top,metricsorlimitarguments. The service ranks at most 20 groups. -
Only if prevalence or mean evidence is needed and statistics is advertised:
get_attribute_statistics {S,attributeName:A,filterOptions:F,itemsPerPage:5,itemsToSkip:0,metricToSortBy:"CaseFrequency",sortOrder:"Descending"}. Match returned values explicitly. Influence-ranked groups may differ from frequency-ranked groups; an absent match is unknown, not zero. -
For a remaining hypothesis, use a discriminating matched comparison via compare-cohorts, focused statistics/cases, or another relevant candidate. Derive each test from frozen F, never an outcome-only exploratory subset. A cached signal can go directly to its test. Continue needed checks/pages without fixed analytical-call or candidate quotas. If matched evidence contradicts the proposed direction, mark it contradicted within that scope; do not privilege the earlier influence score or claim it proves a cause.
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.
- 9d ago First seen · 58 lines · 25 tokens per session scan A 296d49b11900
analyze-drivers is a skill published in the GitHub repository microsoft/power-platform-skills (1,016 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 745 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-10-09.
Other skills, from other repositories
canvas-apps-ui-gen
Generates paste-ready Power Apps Canvas App YAML. Invoke when the user wants to replicate a UI mockup, improve an existing Canvas app screen, or build a new screen from a text description. Also invoke when the user asks to "improve", "redesign", or "generate YAML" for a Canvas app screen.
top-design
Create award-winning, immersive web experiences at the level of Awwwards-featured agencies. Use when the user mentions "Awwwards quality", "make my site stunning", "scroll animations", "parallax storytelling", "cinematic web design", "portfolio site", or "brand experience". Also trigger when elevating a standard…
ux-heuristics
Evaluate and improve interface usability using heuristic analysis. Use when the user mentions "usability audit", "users are confused", "form usability", "navigation problems", "Nielsen heuristics", "cognitive walkthrough", or "is this easy to use". Also trigger when reviewing a design for usability issues, improving…
blue-ocean-strategy
Create uncontested market space using value innovation instead of competing head-to-head. Use when the user mentions "blue ocean", "red ocean", "strategy canvas", "ERRC framework", "value innovation", "non-customers", "buyer utility map", "the market is too crowded", "how do we stand out", or "escape the price war".…
clean-code
Write readable, maintainable code through disciplined naming, small functions, and clean error handling. Use when the user mentions "clean up this code", "this function is too long", "code smells", "naming conventions", "boy scout rule", "single responsibility", or "unit test quality". Also trigger when reviewing a…
session-scan
Compute metrics for Claude Code sessions. Discovers via ccrider, filters trivial, computes friction/opportunity/fingerprint scores. Use for broad session triage.