---
title: "Undominated · Test-Time Compute ROI Audit: review, setup & limitations · Undominated.ai"
canonical: https://undominated.ai/skills/undominated-test-time-compute-roi-audit/
description: "Calculates cost-per-accuracy return curves for Best-of-N sampling, search depth scaling, and verifier reranking vs base model upgrading."
---

# Undominated · Test-Time Compute ROI Audit: review, setup & limitations · Undominated.ai

> Calculates cost-per-accuracy return curves for Best-of-N sampling, search depth scaling, and verifier reranking vs base model upgrading.

[← Explore all skills](/skills/)

EVIDENCE AND EVALUATION / Undominated.ai

# Undominated · Test-Time Compute ROI Audit

Calculates cost-per-accuracy return curves for Best-of-N sampling, search depth scaling, and verifier reranking vs base model upgrading.

 [See setup guidance ↓](#setup)[Original source ↗](https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/definition.md)

SOURCE REVIEW

 Reviewed 2026-10-14
 Evidence 3 linked sources
 Publisher Undominated.ai
 Licence [MIT ↗](https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/LICENSE.txt)
 Revision cb5adc4e6f02
 [Read what was—and wasn’t—checked ↓](#review)

“Calculates cost-per-accuracy return curves for Best-of-N sampling, search depth scaling, and verifier reranking vs base model upgrading.”

 [Undominated.ai · upstream description ↗](https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/definition.md) Our analysis follows below.

01 / THE REASONING

## Why this made the selection.

 - Pairs a bounded workflow with an offline Python checker and explicitly synthetic example inputs.
- Created for recurring evidence and comparison failures: missing facts remain unknown and every conclusion keeps its scope.
- It names a concrete failure mode: Determine whether scaling test-time search delivers higher accuracy per dollar than migrating to a larger frontier model.

### A good fit for

 - Determine whether scaling test-time search delivers higher accuracy per dollar than migrating to a larger frontier model.
- Run the local checker against a supplied file for this stated condition: FAILED: BoN accuracy {bon_acc} does not meet frontier baseline {front_acc}.

### Weigh up before choosing

 - Evaluates candidate generation and verifier pricing. Assumes calibrated reward model ranking.
- Fixture checks establish the documented local behaviour, not performance on an unrestricted set of real tasks.
- Public GitHub source availability is not yet verified; the complete download contains the reviewed source.
- A new npm install path is not yet verified. Use the complete source download.
- `2`: Schema error or invalid usage.

02 / THE REVIEW RECORD

## What we actually inspected.

Source review has boundaries. A clear record is more useful than a “safe” badge.

### Material inspected

 - skills/undominated-test-time-compute-roi-audit/SKILL.md
- skills/undominated-test-time-compute-roi-audit/scripts/check.py
- skills/undominated-test-time-compute-roi-audit/examples/synthetic.json

### Our findings

 - First-party resource authored by Undominated.ai; this is our own verification record, not an independent endorsement.
- The download preserves the complete source and supporting files. Its manifest hashes identify the exact bytes.
- The checker names its required fields as: required = ["n_candidates", "base_pass_rate", "bon_pass_rate", "token_cost_per_candidate_usd", "verifier_cost_per_candidate_usd", "frontier_single_pass_cost_usd", "frontier_single_pass_accuracy", "max_allowed_bon_total_cost_usd"].
- The checker rejects the run rather than passing: FAILED: BoN accuracy {bon_acc} does not meet frontier baseline {front_acc}.

### Not established by this review

 - Model compliance with these instructions on arbitrary tasks
- Native integration in every agent host
- Public GitHub source identity
- Remote installation through the standard Skills CLI
- The new npm resource CLI installation

The review applies to the material and revision named here. A newer upstream release can change its behavior.

03 / PUT IT TO WORK

## Add a skill to your workflow.

[Upstream setup instructions ↗](https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/definition.md)
 - Download the complete bundle from https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/bundle.zip and extract it into a new directory.
- Place the extracted directory at .agents/skills/undominated-test-time-compute-roi-audit/ or your host's documented skills directory. Preserve SKILL.md, scripts, examples and licence files together.
- Run the documented synthetic example from the skill directory with Python 3.10 or later before using your own evidence.

### Before you start

 - An Agent Skills compatible host
- Python 3.10 or later for the optional checker

### Compatibility

Agent Skills compatible hosts · Python 3.10+

### Implementation

Python · Markdown

### Local, explicit inputs

 - read:user-selected-local-file

### Cost model

MIT source at no charge. Your agent host or model provider may charge for use; the included offline checks require no paid API.

THE COMPLETE REVIEWED DEFINITION

## Read it before you reuse it.

Original source bytes, with attribution. Review the host-specific setup notes above.

 Copy definition ↗ [Download complete resource + licence ↗](/resources/skills/undominated-test-time-compute-roi-audit/bundle.zip)[Raw Markdown ↗](/resources/skills/undominated-test-time-compute-roi-audit/definition.md)
 # Test-Time Compute ROI Audit

## Description
Calculates cost-per-accuracy return curves for Best-of-N sampling, search depth scaling, and verifier reranking vs base model upgrading.

## Category
`reasoning`

## Tags
`test-time-compute`, `best-of-n`, `verifier`, `reasoning`, `roi`

## When to Use
Determine whether scaling test-time search delivers higher accuracy per dollar than migrating to a larger frontier model.

## Operational Limitations
Evaluates candidate generation and verifier pricing. Assumes calibrated reward model ranking.

## Verification Script
Run the deterministic verification checker:
```bash
python3 scripts/check.py examples/synthetic.json
```
Exit codes:
- `0`: Check passed and thresholds satisfied.
- `1`: Threshold breach or operational violation detected.
- `2`: Schema error or invalid usage.

The download contains SKILL.md . Extract the whole bundle; the supporting files are required. Inspect the included MANIFEST.json for file hashes.

By **Undominated.ai**. [Exact upstream source ↗](https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/definition.md) · [Licence](/resources/skills/undominated-test-time-compute-roi-audit/LICENSE.txt) · [Attribution](/resources/skills/undominated-test-time-compute-roi-audit/ATTRIBUTION.txt)

SHA-256 cb5adc4e6f025414a3c213036c0be0af915e9200f41ad2f8295338bfe169f841

 Read the applicable licence MIT License

Copyright (c) 2026 Undominated.ai

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

04 / FOLLOW THE EVIDENCE

## The source trail.

Our notes are separate from the original resource. Check upstream before adopting a new version.

 - [Original Undominated definition ↗](https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/definition.md) Checked 2026-10-07 https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/definition.md Supports: Workflow and input requirements, Stated limitations
- [MIT licence ↗](https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/LICENSE.txt) Checked 2026-10-07 https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/LICENSE.txt Supports: Redistribution terms and attribution
- [Complete source bundle ↗](https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/bundle.zip) Checked 2026-10-07 https://undominated.ai/resources/skills/undominated-test-time-compute-roi-audit/bundle.zip Supports: Full local source, supporting files and integrity manifest

KEEP COMPARING

## Other approaches to consider.

Related by category or shared topics. These are alternatives to inspect, not a measured quality order.

 [### Undominated · Test-time search budget audit ↗ Audits test-time compute search budgets to ensure marginal accuracy gains justify token expenditure.](/skills/undominated-test-time-search-budget-audit/)[### Undominated · Verifier Consensus Cost Audit ↗ Calculates token expenditures and marginal certainty of majority voting consensus across parallel reasoning traces.](/skills/undominated-verifier-consensus-cost-audit/)[### Undominated · Few-Shot Example Pruning Audit ↗ Calculates the marginal accuracy contribution per few-shot exemplar to eliminate low-ROI prompt tokens.](/skills/undominated-few-shot-example-pruning-audit/)

 [AI Tools ↗](/tools/)[Skills ↗](/skills/)[Agents ↗](/agents/)[MCP Servers ↗](/mcp-servers/)[Workflows ↗](/workflows/)

## Continue your investigation

 - [Choose a toolkit](/tools/)
- [Inspect execution hosts](/agents/)
- [Check tool access](/mcp-servers/)
- [Check project dependencies](/check-repo/)
