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 macintog/codex-spine --skill performance-tradeoffgit clone --depth 1 https://github.com/macintog/codex-spineWrote 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/macintog/codex-spine/performance-tradeoff)<a href="https://agentmods.dev/skills/macintog/codex-spine/performance-tradeoff"><img src="https://agentmods.dev/badge/skills/macintog/codex-spine/performance-tradeoff/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/macintog/codex-spine/performance-tradeoff"><img src="https://agentmods.dev/badge/skills/macintog/codex-spine/performance-tradeoff.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 | $0.00000 | $0.00591 |
| Opus 5.5 | $0.00000 | $0.00236 |
| Sonnet 5.5 | $0.00000 | $0.00118 |
| Haiku 4.5 | $0.00000 | $0.00059 |
Grade A, and why
performance-tradeoff 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 yesterday.
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
Performance tradeoff
Before a test, replay, evaluation, benchmark, soak or watch runs, write down in one place: the question it settles and the decision that changes; what in the project's current plan or next host makes the number moot; the smallest input that answers it, located from indexes, logs or labels rather than scanned for; the mode (offline, seeking and batched, unless the property is wall-clock); the hardware shape (batched, pipelined, the fastest engine the target has); the estimate as input ÷ measured throughput × runs, from a smoke run; and the stop rule. A run with no written plan is the failure this skill exists to prevent. Thresholds: over about 15 device-minutes, or a 1× replay longer than the event it tests, get the coordinator's or operator's OK first; a serial batch-1 loop on an idle accelerator is a defect to fix before scaling, not a budget.
Before trusting or reporting a number, check:
- Equivalent arms. Only the intended change differs: build, inputs, load, power/thermal state, output quality. Alternate arm order; a cache warmed by one arm contaminates the next.
- Separate regimes. Cold, warm and sustained are different results. Claim a cold-start win only from fresh-cache runs of both arms.
- Noise before change. Compare the delta with each arm's run-to-run spread; overlapping ranges or few samples mean inconclusive. Give latency percentiles with sample counts.
- Completion, not enqueue. Time async/GPU work to completion, with identical sync and transfer boundaries in both arms.
- Raw-value arithmetic. Relative change = (candidate − baseline) / baseline, direction stated; recheck supplied percentages. No speedup against a timeout or OOM.
- One memory scope. Don't sum overlapping counters (a unified-memory footprint may already include GPU allocations). Headroom is peak versus what the target actually has free; note the sampling interval.
- Phase is not end to end. A faster component isn't a faster request until measured; overlapping work doesn't add serially.
Decide in order: correctness and quality; whether the change enables a supported workload the baseline fails or nearly fails; absolute user-visible cost; maintenance cost. A resource reduction that enables nothing measured doesn't justify a latency, quality or complexity cost. Set thresholds and margins before seeing candidate results.
Answer accept, reject or unproven per hardware and workload case, naming the smallest missing measurement. Report only the metrics that decide it.
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.
- yesterday Changed · +2 lines fe7f7b2c9911
- 19d ago Changed · -57 lines · -83 tokens per session 5a5008f5dbfe
- 1mo ago First seen · 78 lines · 83 tokens per session scan A dd5ce4d0bf15
performance-tradeoff is a skill published in the GitHub repository macintog/codex-spine (12 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 591 tokens. 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 2026-09-19.
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