AI for Research Efficiency, In Practice: Check your proposal against the rules
Narration: an AI-generated voice (ElevenLabs).

[0:00] Eight problems, one check
In one of the Department of Agriculture's grant programs, an application over its page limit, or outside its rules for margins and type size, is returned without review.
N S F says plainly that its submission system doesn't check every rule.
So we planted eight problems in a proposal, and asked an agent to check it. It found eight of the eight.
AI for Research Efficiency, In Practice: check your proposal against the rules.
In this film, an agent checks your own proposal against the call and the funder's current guide, before you submit.
It measures the files and quotes the rules. It never changes a file or writes a word of the proposal.
It builds on episodes four and nine, on small habits and on your data.

[0:55] 1. Ask for the process
The proposal is invented for this film: an N S F CAREER proposal about rice, water and greenhouse gases.
In Codex, in plan mode, the request is a question. What is the best way to check this proposal against everything the solicitation and the funder require? Do not change it.
It asks no questions. It reads the folder, opens N S F's pages online, and proposes a plan.

[1:24] 2. What the system stops, and what it leaves out
Then three helpers research the options in parallel.
One reads N S F's own list of what its submission system stops, like a project description over fifteen pages, or a web address inside it.
Another looks for what that list leaves out, like the letters, and whether the budget justification agrees with the budget. A third works out how to measure the type, the lines and the margins.
That second list is where the agent helps most. The first, it catches a week before the deadline.

[1:57] 3. The plan, attacked
A reviewer agent then attacks the plan.
The rules move. N S F's guide dates from twenty twenty-four and has been amended twice, and a replacement is planned. Its published list of automatic checks dates from January twenty twenty-three.
So the process reads the current documents every time, and names their versions.
A made-up rule is worse than a missed one, so every finding has to quote its rule, word for word.
And the agent writes none of the proposal. N I H won't count applications substantially developed by A I as the applicant's original ideas.

[2:38] 4. The process, written down as a skill
You choose the plan, and the agent writes it down as a skill: a file it reads, so the same steps run every time.
Then you read it beside your own checklist and ask for eight changes, and the agent rewrites the skill.
The skill builds a table of rules from the documents, each with its section and its exact words.
A script measures every P D F: pages, type sizes, lines per inch, margins and web addresses.
The agent compares the budget with its justification, and the people with their time.
Each finding gets one of two labels: the system would also stop this, or only a person catches this today.

[3:21] 5. The run
The run, replayed from its log: forty-three minutes of work in a copy of the folder outside any repository, sped up.
It fetches N S F's guide, its two supplements and the CAREER solicitation again, checks they match the saved copies, and writes down each version.
It builds two hundred and seventeen rules, and the quote check finds all two hundred and seventeen quotations, word for word.
The script measures all eleven files. Then the agent reads the description, the budget and the letters side by side.
Then it writes the report: each finding with its file and page, the rule's own words, and one of the two labels.
Midway through, it notes that the budget's totals add up, but the justification asks for two graduate assistants where the form budgets one, and for more travel than the form.

[4:16] 6. Checked against the answer key
Now the check that doesn't rest on the agent's word: the answer key, written before the run and kept out of the agent's folder.
It found eight of the eight. It missed none.
Three of the eight are on N S F's published list of checks its system makes: the sixteen pages, the heading, and the web address.
The other five aren't on that list, so you can't count on the system to catch them: ten-point type, the missing headings in Prior Support, two budget lines the justification doesn't match, and a letter that praises the proposal where the rules ask for one sentence of intent.
And its labels agree with the key on all eight.
A second agent, in a fresh session, re-checked every quoted rule and the report's measurements. Nothing failed.
And our own script found every quoted rule in N S F's documents. The report flagged none of the eleven decoys: things that look wrong, but the rules allow.

[5:16] Same process, another funder
The same skill works for other funders. For the Agriculture and Food Research Initiative, the narrative can run eighteen pages, in twelve-point type.
Checked against those rules, the same project description fits the eighteen pages, but its ten-point type breaks the twelve-point rule, and it lacks the header N I F A asks for.

[5:40] The line not to cross
Use it on your own proposal only. N I H bars A I from review critiques, and N S F bars reviewers from putting proposals into unapproved A I tools.
Unpublished ideas can be data your campus protects, so use a tool your campus approves. And the grants office still has the last word.

[6:04] Try it
Try it on the practice proposal first. The folder and the skill are on the page, for Codex, Antigravity and Claude Code.

[6:19] Review and next
Ask for the process, check every finding's quote, and run the skill on your own proposal a week before the deadline.
More films for this shelf are on the way.