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 yeaight7/agent-powerups --skill architecture-decision-recordsgit clone --depth 1 https://github.com/yeaight7/agent-powerupsWrote 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/yeaight7/agent-powerups/architecture-decision-records)<a href="https://agentmods.dev/skills/yeaight7/agent-powerups/architecture-decision-records"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/architecture-decision-records/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/yeaight7/agent-powerups/architecture-decision-records"><img src="https://agentmods.dev/badge/skills/yeaight7/agent-powerups/architecture-decision-records.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 | $0.00042 | $0.00671 |
| Opus 5.5 | $0.00017 | $0.00268 |
| Sonnet 5.5 | $0.00008 | $0.00134 |
| Haiku 4.5 | $0.00004 | $0.00067 |
Grade A, and why
architecture-decision-records 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Code tells you how a system works. ADRs tell you why it works that way, preventing future maintainers (and AI agents) from suggesting "improvements" that were already tried and discarded.
When to Use
- Finalizing a major design decision (e.g., "Choosing Postgres over MongoDB", "Using custom event bus over Redis")
- Reversing or superseding a previous decision
- A reviewer or agent proposes a change that contradicts an existing constraint
Inputs
- The decision, the alternatives considered, and the constraints that drove it
- The ADR directory (conventionally docs/adr/)
Workflow
-
Check for an existing ADR first — the decision may already be recorded or superseded:
ls docs/adr/ # existing records rg -ln "<topic keyword>" docs/adr/ # is this decision already covered? -
Create the record at
docs/adr/YYYY-MM-DD-<short-title>.md— date-prefixed for ordering, kebab-case title. -
Fill the structure — keep it under 300 words; focus on constraints, not theory:
# <Decision title> ## Status Accepted | Superseded by <newer ADR filename> ## Context What is the problem? What constraints apply? ## Decision What are we doing? ## Consequences What trade-offs are we accepting? What becomes harder? -
Handle supersession explicitly. When reversing a decision, do NOT edit history: write a new ADR, mark the old one "Superseded by" with a link to the new file, and state what changed.
-
Link from where the decision bites — a one-line pointer near the affected module or in the architecture doc, so the why is discoverable from the how.
Output
- A dated ADR file with Status / Context / Decision / Consequences
- Superseded ADRs updated with forward links — never deleted or rewritten
Verification
- File saved under docs/adr/ with a date-prefixed kebab-case name
- Status, Context, Decision, and Consequences sections all present; body under ~300 words
- Consequences state real trade-offs, not just benefits
- Superseded decisions marked and forward-linked, not edited or removed
- Decision discoverable from the affected code or architecture doc
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 · 73 lines · 42 tokens per session scan A 7c9bdbe0b4fa
architecture-decision-records is a skill published in the GitHub repository yeaight7/agent-powerups (6 stars, last pushed 19d ago), licensed Apache-2.0. It adds 42 tokens to every session and 671 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 2026-09-14.
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