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 mawildoer/atopile-agent-skill --skill trade-studygit clone --depth 1 https://github.com/mawildoer/atopile-agent-skillWrote 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/mawildoer/atopile-agent-skill/trade-study)<a href="https://agentmods.dev/skills/mawildoer/atopile-agent-skill/trade-study"><img src="https://agentmods.dev/badge/skills/mawildoer/atopile-agent-skill/trade-study/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/mawildoer/atopile-agent-skill/trade-study"><img src="https://agentmods.dev/badge/skills/mawildoer/atopile-agent-skill/trade-study.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 | $0.00078 | $0.00901 |
| Opus 5 | $0.00039 | $0.00451 |
| Sonnet 5 | $0.00016 | $0.00180 |
| Haiku 4.5 | $0.00008 | $0.00090 |
Grade A, and why
trade-study 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 10d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trade Studies
Trade studies capture structured comparisons when a design decision has multiple viable options. They make reasoning auditable for the team now and anyone revisiting the decision later.
When to Write One
Write one when:
- Multiple options are viable and the best choice depends on weighing competing priorities
- The decision affects downstream work (connector choice constrains PCB stackup, firmware, mechanical design)
- The decision is hard to reverse once implemented
Don't write one when:
- One option is clearly dominant
- The decision is easily reversible
- The scope is too small to justify the overhead
File Convention
Each trade study is a markdown file, dated and kebab-cased, kept in the repo (e.g. under docs/trades/):
docs/trades/YYYY-MM-DD-<topic-in-kebab-case>.md
Structure
Every trade study has exactly four sections plus a header block:
Header Block
# Trade Study: <Title>
**Date:** YYYY-MM-DD
**Status:** OPEN | DECIDED
**Decision:** <one-line summary of chosen option> ← only after decided
1. Context
What we're deciding and why it matters. Include:
- The problem or constraint that forced the decision
- Requirements the solution must meet (quantified where possible)
- Use cases affected by the decision
2. Options
Each viable approach as a subsection (### Option A: ...). Describe concisely — what the approach is, how it works, key characteristics. No advocacy — just facts.
3. Comparison Table
Rows are evaluation criteria, columns are options. Use qualitative ratings with explanation, not bare checkmarks.
| Criteria | A: <name> | B: <name> |
|---|---|---|
| **<criterion>** | <rating + explanation> | <rating + explanation> |
Good criteria to consider for hardware decisions:
- JLCPCB/LCSC availability and stock
- Board space impact (mm² estimate)
- Component count / BOM cost
- ADC channels, MCU peripherals consumed
- New packages required (
ato create part) - Accuracy / precision at operating conditions
- Temperature drift behavior
- Failure modes and detectability
- Firmware complexity
- Reusability across other designs
- Power sequencing / hot-swap implications
- Mechanical constraints (PCB thickness, connector alignment)
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.
- 10d ago First seen · 106 lines · 78 tokens per session scan A 20df4fcc6490
trade-study is a skill published in the GitHub repository mawildoer/atopile-agent-skill (10 stars, last pushed 2mo ago), licensed MIT. It adds 78 tokens to every session and 901 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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