---
title: "Undominated · Cross modal KV allocation audit: review, setup & limitations · Undominated.ai"
canonical: https://undominated.ai/skills/undominated-cross-modal-kv-allocation-audit/
description: "Audits visual token versus text token KV cache allocation ratios in long multimodal conversations."
---

# Undominated · Cross modal KV allocation audit: review, setup & limitations · Undominated.ai

> Audits visual token versus text token KV cache allocation ratios in long multimodal conversations.

[← Explore all skills](/skills/)

EVIDENCE AND EVALUATION / Undominated.ai

# Undominated · Cross modal KV allocation audit

Audits visual token versus text token KV cache allocation ratios in long multimodal conversations.

 [See setup guidance ↓](#setup)[Original source ↗](https://undominated.ai/resources/skills/undominated-cross-modal-kv-allocation-audit/definition.md)

SOURCE REVIEW

 Reviewed 2026-10-14
 Evidence 3 linked sources
 Publisher Undominated.ai
 Licence [MIT ↗](https://undominated.ai/resources/skills/undominated-cross-modal-kv-allocation-audit/LICENSE.txt)
 Revision 7c192af46b2d
 [Read what was—and wasn’t—checked ↓](#review)

“Audits visual token versus text token KV cache allocation ratios in long multimodal conversations.”

 [Undominated.ai · upstream description ↗](https://undominated.ai/resources/skills/undominated-cross-modal-kv-allocation-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: Verifies total VRAM footprint across modality caches; does not compute attention weights.

### A good fit for

 - Audit multi-turn vision-language models to prevent visual tokens from exhausting available VRAM.
- Run the local checker against a supplied file for this stated condition: FAILED: Multimodal KV cache {vram}MB exceeds limit {limit}MB.

### Weigh up before choosing

 - Verifies total VRAM footprint across modality caches; does not compute attention weights.
- 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-cross-modal-kv-allocation-audit/SKILL.md
- skills/undominated-cross-modal-kv-allocation-audit/scripts/check.py
- skills/undominated-cross-modal-kv-allocation-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: req = ["vision_kv_mb", "text_kv_mb", "total_vram_mb", "utilization_percent", "max_vram_limit_mb"].
- The checker rejects the run rather than passing: FAILED: Multimodal KV cache {vram}MB exceeds limit {limit}MB.

### 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-cross-modal-kv-allocation-audit/definition.md)
 - Download the complete bundle from https://undominated.ai/resources/skills/undominated-cross-modal-kv-allocation-audit/bundle.zip and extract it into a new directory.
- Place the extracted directory at .agents/skills/undominated-cross-modal-kv-allocation-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-cross-modal-kv-allocation-audit/bundle.zip)[Raw Markdown ↗](/resources/skills/undominated-cross-modal-kv-allocation-audit/definition.md)
 # Cross modal KV allocation audit

## Description
Audits visual token versus text token KV cache allocation ratios in long multimodal conversations.

## Category
`serving`

## Tags
`serving`, `multimodal`, `kv-cache`, `vram`, `allocation`

## When to Use
Audit multi-turn vision-language models to prevent visual tokens from exhausting available VRAM.

## Operational Limitations
Verifies total VRAM footprint across modality caches; does not compute attention weights.

## 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-cross-modal-kv-allocation-audit/definition.md) · [Licence](/resources/skills/undominated-cross-modal-kv-allocation-audit/LICENSE.txt) · [Attribution](/resources/skills/undominated-cross-modal-kv-allocation-audit/ATTRIBUTION.txt)

SHA-256 7c192af46b2d8ec5c8ab06430a57d64761aa55527cff21195db73321314b40f5

 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-cross-modal-kv-allocation-audit/definition.md) Checked 2026-10-07 https://undominated.ai/resources/skills/undominated-cross-modal-kv-allocation-audit/definition.md Supports: Workflow and input requirements, Stated limitations
- [MIT licence ↗](https://undominated.ai/resources/skills/undominated-cross-modal-kv-allocation-audit/LICENSE.txt) Checked 2026-10-07 https://undominated.ai/resources/skills/undominated-cross-modal-kv-allocation-audit/LICENSE.txt Supports: Redistribution terms and attribution
- [Complete source bundle ↗](https://undominated.ai/resources/skills/undominated-cross-modal-kv-allocation-audit/bundle.zip) Checked 2026-10-07 https://undominated.ai/resources/skills/undominated-cross-modal-kv-allocation-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 · H2O heavy hitter eviction audit ↗ Audits Heavy Hitter Oracle (H2O) KV cache eviction and critical prompt token retention under memory limits.](/skills/undominated-h2o-heavy-hitter-eviction-audit/)[### Undominated · KV Cache Memory Sizing Audit ↗ Audits KV cache memory footprint per token and max concurrent sequence limits under FP16, FP8, and INT4 KV caches to prevent serving OOMs.](/skills/undominated-kv-cache-sizing-audit/)[### Undominated · PyramidKV layer budget audit ↗ Audits PyramidKV non-uniform layer cache allocations to verify total VRAM budget compliance.](/skills/undominated-pyramidkv-layer-budget-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/)
