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 compare-cohortsgit 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/compare-cohorts)<a href="https://agentmods.dev/skills/microsoft/power-platform-skills/compare-cohorts"><img src="https://agentmods.dev/badge/skills/microsoft/power-platform-skills/compare-cohorts/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/compare-cohorts"><img src="https://agentmods.dev/badge/skills/microsoft/power-platform-skills/compare-cohorts.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 | $0.00023 | $0.00777 |
| Opus 5.5 | $0.00009 | $0.00311 |
| Sonnet 5.5 | $0.00005 | $0.00155 |
| Haiku 4.5 | $0.00002 | $0.00078 |
Grade A, and why
compare-cohorts 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 — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Matched cohort comparisons
Use the shared contract and filters/units. Fix the outcome definition/provenance, metric, aggregation, units, timezone and one selector S. Freeze the user's agreed baseline F, separately from current exploratory filters. Reuse metadata versions and exact typed cohort values. Use the investigation method for findings/status.
Ordered trace
- Copy baseline F twice. For attribute cohorts append
{attributeName:A,dataType:T,attributeValues:[X],isInclusive:true}toattributeValueFiltersfor A's cohort value, and the same shape with Y for B. Preserve other agreed baseline conditions; retain rework restrictions only if part of that baseline. Do not leak an exploratory/outcome-only subset into a full-population comparison. Change only the intended cohort condition. If values are unknown, requestget_attribute_values_v2 {S,attributeName:A,itemsPerPage:20,itemsToSkip:0,filterOptions:F}; it returns values, not frequencies. get_process_overall_metrics_v2 {S,filterOptions:F_A}->get_process_overall_metrics_v2 {S,filterOptions:F_B}. Nometrics,groupByor aggregation parameter exists. Use the same returned metric definitions; nativeCaseDuration/CaseWaitingTimeare means.- Only if a grouped explanation is needed and statistics is advertised, make a matched pair:
get_attribute_statistics {S,attributeName:A,filterOptions:F_A,itemsPerPage:5,itemsToSkip:0,metricToSortBy:"TotalDuration",sortOrder:"Descending"}, then exactly the same call with F_B. Do not treat independent top-five pages as a complete aligned population.
Continue relevant value/group pages or matched follow-ups when needed, without fixed call quotas. Stop at sufficient evidence, no new information or a capability/error boundary; no blind sweeps. Do not create views or use two inclusive timeframes in one query as an A/B comparison.
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 · 60 lines · 23 tokens per session scan A 220fd9f5d174
compare-cohorts is a skill published in the GitHub repository microsoft/power-platform-skills (1,016 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 777 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.
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