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 functional-plannergit 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/functional-planner)<a href="https://agentmods.dev/skills/microsoft/hve-core/functional-planner"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/functional-planner/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/functional-planner"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/functional-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 31 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 36 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00035 | $0.02992 |
| Opus 5.5 | $0.00014 | $0.01197 |
| Sonnet 5.5 | $0.00007 | $0.00598 |
| Haiku 4.5 | $0.00003 | $0.00299 |
Grade A, and why
functional-planner 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 2mo 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 — 161 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Functional Planner
Read-only, platform-agnostic conventions for turning a Product Requirements Document (PRD) into a validated work-item hierarchy that a separate execution pass creates. This skill owns the decomposition core: how a PRD is analyzed across phases, how a candidate hierarchy is validated against a target platform's supported types, which open planning-framework lens shapes the decomposition, and how the plan is handed off. It never creates, updates, transitions, comments on, or links a work item on any platform.
When to Use
Use this skill when planning a work-item hierarchy from a PRD or requirements artifact for a supported platform, ahead of execution:
- PRD-to-work-item planning — map a PRD into a validated Epic/Feature/Story (or Epic/Story/Task) hierarchy for a separate execution pass.
- Hierarchy refinement — reconcile a candidate hierarchy against a platform's supported types and an existing backlog.
For discovery, triage, and execution of the resulting plan, hand off to the backlog-management skill and the Backlog Manager agent. This skill produces planning-only artifacts and stops at a reviewable handoff.
Invocation
When invoked directly as a command, resolve these before Phase 1:
| Argument | Resolution |
|---|---|
| PRD source | The supplied artifact path, folder, attached file, or explicit PRD content. When omitted, fall back only to a concrete PRD source artifact in the active file or current context. |
| Platform | The supplied target platform, or the tracker resolved from workspace context. Determines which per-platform reference applies. |
| Scope | The target project, owner/repo, or project key used for type validation, label or field confirmation, and related-item discovery. |
| Autonomy | The review-gate level for the resulting handoff, defaulting to partial. |
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 161 lines · 35 tokens per session scan A 63ef2f04edce
functional-planner is a skill published in the GitHub repository microsoft/hve-core (1,606 stars, last pushed today), licensed MIT. It adds 35 tokens to every session and 2,992 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 2026-08-30.
functional-planner compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| functional-plannermicrosoft/hve-core | Skill | 1.6k | today | MIT | A | 35 | 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 |