Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add testdouble/han/plugin install han-documentationWrote 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/testdouble/han/architectural-decision-record)<a href="https://agentmods.dev/skills/testdouble/han/architectural-decision-record"><img src="https://agentmods.dev/badge/skills/testdouble/han/architectural-decision-record/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/testdouble/han/architectural-decision-record"><img src="https://agentmods.dev/badge/skills/testdouble/han/architectural-decision-record.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 | $0.00094 | $0.03553 |
| Opus 5.5 | $0.00038 | $0.01421 |
| Sonnet 5.5 | $0.00019 | $0.00711 |
| Haiku 4.5 | $0.00009 | $0.00355 |
Grade A, and why
architectural-decision-record 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 1mo 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 — 231 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create ADR
Operating Principles
- YAGNI applies to ADRs themselves. Apply the evidence-based YAGNI rule from ../../references/yagni-rule.md. An ADR is worth recording only when there is a concrete forcing function today — a real decision the team is actively making, an existing code path or architectural choice that will be locked in by this record, an applicable regulation, a customer commitment, or a documented incident that drove the choice. ADRs about decisions that don't have to be made yet, "for future flexibility", "best practice says we should pick X", or symmetry with other ADRs ("we have one for auth, so we should have one for billing") are YAGNI candidates and the ADR should not be written. When proposed, recommend deferral with the trigger that would justify writing the ADR (a real decision arising, a real incident, a real regulation taking effect). The user always wins; the rule's job is to make the cost of writing speculative architectural records visible — every ADR is a future-reader's load and a pattern future agents will treat as committed.
- The companion evidence rule applies to the ADR's supporting evidence. Apply the evidence rule from ../../references/evidence-rule.md to the citations that justify the ADR's decision and rejected alternatives. Name the trust class of each citation (codebase, web, provided); mark single-source web claims that drive the chosen option; and when no evidence at any tier supports a claimed trade-off, label it rather than presenting it as a weak preference.
- The readability rule shapes the ADR's prose. Source the standard by invoking
han-communication:readability-guidanceand apply it as you write the ADR. Hold its default audience frame: a capable reader who did not make this decision and lacks your context. The frame governs how each section reads, never whether a required technical fact appears.
What ships with it
2 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.
- 1mo ago First seen · 231 lines · 94 tokens per session scan A aa396f931ac4
architectural-decision-record is a skill published in the GitHub repository testdouble/han (323 stars, last pushed 9d ago), licensed MIT. It adds 94 tokens to every session and 3,553 once invoked, about $0.0004 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 2026-09-03.
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