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 copilot-otel-metricsgit 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/copilot-otel-metrics)<a href="https://agentmods.dev/skills/microsoft/hve-core/copilot-otel-metrics"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/copilot-otel-metrics.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to high
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 →
- high Privilege Escalation · line 94 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium Prompt Injection · line 112 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 119 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 121 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 122 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 127 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 | $0.00047 | $0.03040 |
| Opus 5 | $0.00023 | $0.01520 |
| Sonnet 5 | $0.00009 | $0.00608 |
| Haiku 4.5 | $0.00005 | $0.00304 |
Grade A, and why
copilot-otel-metrics 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copilot OpenTelemetry Metrics
Goal
Take the user from "I want Copilot telemetry" to telemetry they can query. Do the work for them where doing it is safe and reversible, and walk them through it where it is not.
Done means export is enabled in the settings file that actually resolves, a backend is receiving data, a dashboard exists for that backend, and the user has confirmed data landed by querying the store rather than by trusting an HTTP 200.
Modes
Modes are independent. A user may run one, several, or all. Local capture and organization capture are separate journeys, not stages of the same one.
| Mode | Use when the user wants to | Consent gate | Reference |
|---|---|---|---|
local-setup |
Turn on Copilot's OTel export on this machine | Show the exact settings diff and write only after approval | references/local-setup.md |
local-stack |
Get a backend on this machine to receive it | Write the files, then hand over the command; never run it | references/local-stack.md |
org-distribution |
Push OTel settings to a fleet of developers | Nothing is applied; draft the configuration and explain it | references/org-distribution.md |
azure-capture |
Collect a fleet's telemetry into Azure and chart it | Write the templates, then hand over the deploy commands | references/azure-capture.md |
references/verification.md is shared by every mode. Read it before telling anyone their telemetry works.
When the request names a goal rather than a mode, pick the mode that reaches the goal and say which one was picked. "Set up Copilot metrics" with no other context means local-setup followed by local-stack. Confirm before assuming the organization path, because it spends money and places a shared write credential on every workstation.
What ships with it
42 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.
- examples/_input_policy.py 11 KB runs code
- examples/azure/agent-host-relay/compose.yaml 2.5 KB
- examples/azure/agent-host-relay/otel-collector-config.yaml 6.3 KB
- examples/azure/deploy.sh 4.0 KB runs code
- examples/azure/main.bicep 5.0 KB
- examples/azure/main.tf 3.4 KB
- examples/azure/otel-collector-config.yaml 7.7 KB
- examples/azure/outputs.tf 836 B
- examples/azure/README.md 14 KB
- examples/azure/variables.tf 1.9 KB
- examples/azure/versions.tf 444 B
- examples/baseline.py 6.9 KB runs code
- examples/compose.yaml 5.1 KB
- examples/dashboards/copilot-otel-azure.json 10 KB
- examples/dashboards/copilot-otel.json 22 KB
- examples/inspect_metrics.py 3.2 KB runs code
- examples/otel-collector-local.yaml 5.9 KB
- examples/README.md 10 KB
- examples/settings_upsert.py 27 KB runs code
- examples/validate_dashboard.py 13 KB runs code
- examples/verify.py 8.7 KB runs code
- pyproject.toml 929 B
- references/azure-capture.md 19 KB
- references/local-setup.md 13 KB
- references/local-stack.md 14 KB
- references/org-distribution.md 7.0 KB
- references/verification.md 9.2 KB
- SECURITY.md 103 KB
- tests/_config_support.py 12 KB runs code
- tests/corpus/0_empty 0 B
- tests/corpus/1_collector_config 186 B
- tests/corpus/2_loopback_url 40 B
- tests/corpus/3_settings_jsonc 164 B
- tests/corpus/4_redaction_keys 93 B
- tests/corpus/5_rejected_url 51 B
- tests/fuzz_harness.py 3.8 KB runs code
- tests/test_azure_templates.py 26 KB runs code
- tests/test_collector_carriers.py 61 KB runs code
- tests/test_helpers.py 38 KB runs code
- tests/test_local_config.py 20 KB runs code
- tests/test_settings_upsert.py 42 KB runs code
- uv.lock 77 KB
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 · 139 lines · 47 tokens per session scan A 0a393c738fb0
copilot-otel-metrics is a skill published in the GitHub repository microsoft/hve-core (1,437 stars, last pushed today), licensed MIT. It adds 47 tokens to every session and 3,040 once invoked, about $0.0002 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 2026-08-30.
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