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 stdin/buy-vs-build --skill buy-vs-build-gaingit clone --depth 1 https://github.com/stdin/buy-vs-buildWrote 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/stdin/buy-vs-build/buy-vs-build-gain)<a href="https://agentmods.dev/skills/stdin/buy-vs-build/buy-vs-build-gain"><img src="https://agentmods.dev/badge/skills/stdin/buy-vs-build/buy-vs-build-gain/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/stdin/buy-vs-build/buy-vs-build-gain"><img src="https://agentmods.dev/badge/skills/stdin/buy-vs-build/buy-vs-build-gain.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 | $0.00044 | $0.00244 |
| Opus 5 | $0.00022 | $0.00122 |
| Sonnet 5 | $0.00009 | $0.00049 |
| Haiku 4.5 | $0.00004 | $0.00024 |
Grade A, and why
buy-vs-build-gain 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 11d 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.
What it actually says
Buy vs Build Gain
Summarize impact from benchmark data without overstating it. Distinguish measured local overhead from behavior benchmarks that still need agent runs.
Workflow
- Read
benchmarks/behavior-cases.jsonfor behavioral test cases. - Run
npm run benchmarkfor local instruction and hook overhead. - If agent-run results exist, report LOC, files changed, dependencies added, decision-note quality, time, token/cost data, and safety regressions.
- If only cases exist, call them a benchmark plan, not measured impact.
Output
Use this shape:
Measured
- <metric>: <value>
Behavior cases
- <case>: expected rung <rung>; baseline risk <risk>
Limitations
- <what has not been measured yet>
Never claim the ruleset reduces LOC, cost, or time until a baseline-vs-enabled agent run has actually been measured.
What ships with it
1 file 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.
- 11d ago First seen · 33 lines · 44 tokens per session scan A d7123f811fb0
buy-vs-build-gain is a skill published in the GitHub repository stdin/buy-vs-build (3 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 244 once invoked, about $0.0002 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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