HVE Core is a collection of agents, prompts, coding instructions, and skills for building repeatable software-development workflows with GitHub Copilot. It is intended for individuals and teams that want structured AI-assisted research, planning, implementation, and review, while the catalogue entries provide many of its reusable workflow 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/hve-core --skill rpigit clone --depth 1 https://github.com/microsoft/hve-coreWrote 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/hve-core/rpi)<a href="https://agentmods.dev/skills/microsoft/hve-core/rpi"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/rpi/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/hve-core/rpi"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/rpi.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 | $0.00045 | $0.07232 |
| Opus 5.5 | $0.00018 | $0.02893 |
| Sonnet 5.5 | $0.00009 | $0.01446 |
| Haiku 4.5 | $0.00005 | $0.00723 |
Grade A, and why
rpi 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 yesterday.
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 — 244 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RPI
Goal
Coordinate a resumable RPI session through Research, Plan, Implement, Review, and Follow-up, whether invoked directly as /rpi, discovered by the model for multi-phase RPI coordination, or preloaded by RPI Agent. Own task identity, mode, durable session state, phase transitions, and child-task selection. Activate the matching phase skill for its work rather than reproducing its procedure.
Success criteria
- Task identity is resolved before recovery and remains stable across state and phase artifacts; unrelated state is left unchanged.
- Progression and decision participation follow confirmed direction. Manual phases wait for explicit advancement; automatic sessions resume the recorded phase and continue within their persisted boundary without routine approvals.
- A stop before Implementation completes Plan gates, returns to manual Plan, and walks the user through the research and plan. Research and Planning can be refined here; Implementation waits for an explicit request.
- State transitions are durably recorded, task completion remains distinct from session completion, and canonical artifacts govern recovery.
- Every task a conversation works on keeps its state in one session folder, parent and child state files link to each other, and an offered canvas shows the session without ever blocking it.
- A session runs at most one plan critique and one post-implementation Review, both in its first task, unless the user asks for more; plan changes and review-driven child loops do not start another. The user can skip either step, and a skipped step is recorded as skipped rather than failed. Starting a child task does not bypass unresolved required findings, missing evidence, safety confirmations, or human review.
- Phase skills own their canonical evidence and gates; the session preserves their state and artifact pointers across transitions.
- Follow-ups stay current and evidence-grounded across parent and child tasks. Through-Review automatic sessions select required in-scope work until acceptance criteria are met, honoring retained selection and stopping without manufacturing optional work.
- Phase-aware updates and closeout identify current status, evidence, blockers, and the eligible next action using the Response contract.
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.
- yesterday First seen · 244 lines · 45 tokens per session scan A e946f00c5d63
rpi is a skill published in the GitHub repository microsoft/hve-core (1,606 stars, last pushed today), licensed MIT. It adds 45 tokens to every session and 7,232 once invoked, about $0.0002 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 2026-11-07.
rpi compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| rpimicrosoft/hve-core | Skill | 1.6k | today | MIT | A | 45 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |