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/sananthanarayan/skilldrop/adr-generatornpx skills add sananthanarayan/skilldrop --skill adr-generatorgit clone --depth 1 https://github.com/sananthanarayan/skilldropWrote 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/sananthanarayan/skilldrop/adr-generator)<a href="https://agentmods.dev/skills/sananthanarayan/skilldrop/adr-generator"><img src="https://agentmods.dev/badge/skills/sananthanarayan/skilldrop/adr-generator.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 | $0.00072 | $0.00763 |
| Opus 5 | $0.00036 | $0.00381 |
| Sonnet 5 | $0.00014 | $0.00153 |
| Haiku 4.5 | $0.00007 | $0.00076 |
Grade A, and why
adr-generator 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 5d 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 — 50 lines — stays where its author put it; the contents beside it link to each section on GitHub.
adr-generator
You help the user produce a clean, properly-numbered Architecture Decision Record.
How to respond
-
Pick the format. Default to MADR (richer, has decision drivers + pros/cons per option). Use Nygard when the user explicitly asks for the "classic" or "simple" ADR, or when the decision is small enough that MADR feels heavyweight.
-
Gather the essentials. Before drafting, make sure you know:
- The decision being made (one sentence — what changed)
- The context / forces (why was a decision needed?)
- The options that were considered (at least 2 — if only one option exists, this isn't really a decision)
- Why the chosen option won (the trade-off)
Ask at most 2 clarifying questions if essentials are missing. Don't fish for nice-to-haves like "decision drivers" — infer reasonable ones from the context.
-
Number it correctly. ADRs are numbered sequentially starting at
0001. Ask the user where their ADRs live (commonlydocs/adr/ordoc/architecture/decisions/) and find the next number by listing the existing files. If no ADRs exist yet, start at0001. -
Pick the filename. Use the slug form:
NNNN-short-title-in-kebab-case.md. Examples:0001-record-architecture-decisions.md0007-use-postgres-as-primary-datastore.md0014-adopt-event-driven-checkout.md
-
Output. Write the file using the appropriate template, then summarize the decision in 2–3 sentences for the chat.
Templates
templates/madr.md— MADR 3.0 format (recommended)templates/nygard.md— Nygard's original (simpler, 4 sections)
Quality bar
- Status must be one of:
Proposed,Accepted,Deprecated,Superseded by ADR-NNNN. Default toProposedunless the user says it's already been agreed. - Title is a noun phrase, not a verb phrase. ✅ "Use Postgres as primary datastore" — ❌ "Decide what database to use".
- Consequences must include trade-offs, not just upsides. If you can't list a downside, the decision wasn't real.
- Reference previous ADRs by number, not by URL, so the cross-references survive folder restructures.
- Don't editorialize. An ADR records what was decided, not what you (the AI) think was wisest.
What ships with it
5 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.
- 5d ago First seen · 50 lines · 72 tokens per session scan A ebc2b54533fd
adr-generator is a skill published in the GitHub repository sananthanarayan/skilldrop (2 stars, last pushed 21d ago), licensed MIT. It adds 72 tokens to every session and 763 once invoked, about $0.0004 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 2026-08-31.
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