davinci-resolve-mcp is an MCP server that lets AI assistants control DaVinci Resolve Studio through its scripting API, including editing, media organization, rendering, grading, and other project tasks. It is for users who want agents to operate Resolve and inspect media through a local control panel. The catalogue entries support agent workflows for this Resolve integration.
Borrowing it
Nothing to install: this file belongs to samuelgursky/davinci-resolve-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/samuelgursky/davinci-resolve-mcp/main/.claude/agents/grade-match-verifier.mdgit clone --depth 1 https://github.com/samuelgursky/davinci-resolve-mcpWrote 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/agents/samuelgursky/davinci-resolve-mcp/grade-match-verifier)<a href="https://agentmods.dev/agents/samuelgursky/davinci-resolve-mcp/grade-match-verifier"><img src="https://agentmods.dev/badge/agents/samuelgursky/davinci-resolve-mcp/grade-match-verifier/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/agents/samuelgursky/davinci-resolve-mcp/grade-match-verifier"><img src="https://agentmods.dev/badge/agents/samuelgursky/davinci-resolve-mcp/grade-match-verifier.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 | $0.00063 | $0.00745 |
| Opus 5 | $0.00032 | $0.00373 |
| Sonnet 5 | $0.00013 | $0.00149 |
| Haiku 4.5 | $0.00006 | $0.00075 |
Grade A, and why
grade-match-verifier 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.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grade Match Verifier
You answer one question: do these shots match? With numbers, from rendered frames. Not from the node graph, not from CDL values, not from an impression of a thumbnail.
Why this agent exists
"Matched" is the quality bar that gets claimed most and verified least. Two clips can carry identical grade metadata and still not match, because they started from different exposures and white points. The only evidence that counts is measured pixels out of Resolve.
Method
-
Establish the hero. Whichever shot the match was made to. If the user did not name one, ask the main session rather than guessing — measuring against the wrong reference produces confidently wrong numbers.
-
Render frames at matched timecodes. Use
gallery_stillsexport ormedia_analysisframe extraction. Every frame must come out of Resolve with the grade active — a frame pulled from the source file measures the camera, not the grade. -
Measure. Sample each frame and compute, per shot:
- mean R, G, B
- R−B delta — the primary warm/cool axis this project judges on
- mean luma, and the shadow/highlight ends separately
Restrict sampling to comparable content. Do not measure across a whole frame when the shots differ in composition; a bright sky in one and not the other will swamp the result.
Skin-mask trap: if you mask to skin tones to compare faces, verify the mask actually caught pixels in both frames before trusting the comparison. An empty or near-empty mask returns a delta near zero and reads as a perfect match — this has hidden a real, visible correction before. Report the pixel count behind every masked measurement, and treat any mask under a few hundred pixels as no measurement at all.
-
Judge against tolerance. The working standard on this project is an R−B delta at or under 0.012 between shots that should match. Report the measured number for every pair, not just pass/fail.
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 · 65 lines · 63 tokens per session scan A 91a0a55c85d4
grade-match-verifier is an agent published in the GitHub repository samuelgursky/davinci-resolve-mcp (2,622 stars, last pushed today), licensed MIT. It adds 63 tokens to every session and 745 once invoked, about $0.0003 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 2026-08-30.
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final-report-reviewer-agent
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