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 agentmods add skills/microsoft/hve-core/adr-authornpx skills add microsoft/hve-core --skill adr-authorgit 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/adr-author)<a href="https://agentmods.dev/skills/microsoft/hve-core/adr-author"><img src="https://agentmods.dev/badge/skills/microsoft/hve-core/adr-author.svg" alt="Measured on agentmods" 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 | $0.00055 | $0.03616 |
| Opus 5 | $0.00028 | $0.01808 |
| Sonnet 5 | $0.00011 | $0.00723 |
| Haiku 4.5 | $0.00006 | $0.00362 |
Grade A, and why
adr-author 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 4d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
adr-author
Overview
This skill encodes the per-phase authoring conventions for Architecture Decision Records consumed by the ADR Creator agent. It also supports direct invocation when no ADR Creator state file exists. Direct callers first run the session recovery and bootstrap protocol from adr-identity.instructions.md: resolve or create .copilot-tracking/adr-plans/{projectSlug}/state.json, confirm entryMode, projectSlug, and outputTemplate, then continue at the phase recorded in state. It supports three entry modes and two output templates and converges all of them at the Govern phase, where the final ADR file is written and lineage is updated atomically.
Entry modes (state.entryMode):
- capture — Interactive authoring driven by user answers to Frame and Decide questions.
- from-planner-handoff — Entry from an upstream planner (Security, RAI, SSSC) with pre-populated Frame fields. Frame still requires user confirmation before exit.
- adopt-template — One-time setup mode that ingests a project's pre-existing ADR template and emits both the first ADR and a committed
.adr-config.yml.
Output templates (state.outputTemplate):
- y-statement — Compact Y-Statement-shaped ADR for low-stakes or reversible decisions. Compressed Frame; ASR triggers optional.
- madr-v4 — Long-form MADR v4.0.0 ADR for architecturally significant decisions. ASR trigger evaluation required during Frame.
Entry mode and output template are independent: a from-planner-handoff session can target either y-statement or madr-v4, and a capture session can do the same. The adopt-template mode produces output shaped by the user's normalized template.
Lifecycle at a glance:
| Mode | Phase sequence | Output |
|---|---|---|
capture |
Frame → Decide → Govern | Shaped by outputTemplate (y-statement or madr-v4) |
from-planner-handoff |
Frame (confirm pre-populated) → Decide → Govern | Shaped by outputTemplate (y-statement or madr-v4) |
adopt-template |
Ingest → Normalize → Derive Questions → Fill → Govern | First ADR + .adr-config.yml per the BYO contract |
What ships with it
32 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.
- pyproject.toml 756 B
- references/asr-trigger-taxonomy.md 5.1 KB
- references/authoring-rubric.md 4.2 KB
- references/lineage-rules.md 4.4 KB
- references/standards-excerpts.md 4.1 KB
- scripts/__init__.py 136 B runs code
- scripts/_utils.py 2.0 KB runs code
- scripts/normalize_template.py 6.9 KB runs code
- scripts/render_template.py 5.2 KB runs code
- scripts/scan_sensitive_content.py 26 KB runs code
- scripts/update_lineage.py 10 KB runs code
- scripts/validate_config.py 2.8 KB runs code
- scripts/validate_frontmatter.py 15 KB runs code
- templates/diagram-ascii.md 1005 B
- templates/diagram-mermaid.md 628 B
- templates/madr-v4-frontmatter-overlay.md 1.7 KB
- templates/madr-v4.md 3.2 KB
- templates/y-statement.md 660 B
- tests/__init__.py 148 B runs code
- tests/conftest.py 3.6 KB runs code
- tests/corpus/0_frontmatter_minimal 46 B
- tests/corpus/1_markdown_anchors 64 B
- tests/corpus/2_slug_valid 31 B
- tests/corpus/README.md 1.0 KB
- tests/fuzz_harness.py 4.2 KB runs code
- tests/test_normalize_template.py 5.5 KB runs code
- tests/test_render_template.py 5.3 KB runs code
- tests/test_scan_sensitive_content.py 32 KB runs code
- tests/test_update_lineage.py 10 KB runs code
- tests/test_utils.py 3.3 KB runs code
- tests/test_validate_frontmatter.py 15 KB runs code
- uv.lock 108 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.
- 4d ago First seen · 180 lines · 55 tokens per session scan A 7cd3e53eed8a
adr-author is a skill published in the GitHub repository microsoft/hve-core (1,422 stars, last pushed today), licensed MIT. It adds 55 tokens to every session and 3,616 once invoked, about $0.0003 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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