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https://github.com/tjhavranek/erc-ai-feedback

Prompt + rubric for AI triage of ERC Starting/Consolidator Grant drafts before peer review. Doesn't replace human reviewers — frees workshop time for what AI can't address.
https://github.com/tjhavranek/erc-ai-feedback

ai-tools claude-code codex erc european-research-council grant-writing peer-review research-support

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Prompt + rubric for AI triage of ERC Starting/Consolidator Grant drafts before peer review. Doesn't replace human reviewers — frees workshop time for what AI can't address.

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README 

          
# erc-ai-feedback



This is a small package for ERC Starting and Consolidator Grant

applicants. It provides a rubric-based pre-review of a draft

proposal that the applicant runs in one chat session with a current

frontier model. The intent is to clear routine structural problems

— vague hypotheses, hidden incrementalism, missing risk logic,

weak panel fit, CV–project disconnect — before workshop time is

spent on them. It does not replace human review. It is for

applicants and applicant-authorised workshop preparation only: do

not use it on a proposal you are evaluating as an ERC panel member

or remote reviewer, since the ERC [prohibits reviewers from

uploading proposals under evaluation to external AI

systems](https://erc.europa.eu/news-events/news/erc-clarifies-limits-ai-use-grant-evaluation).



Two files do the work: the locked evaluation rubric in

[`shared/rubric_locked.md`](shared/rubric_locked.md) and the prompt

in [`basic/prompt.md`](basic/prompt.md). The rubric contains the

verbatim Annex 1 Criterion 1 and Criterion 2 sub-questions from the

ERC *Guide for Peer Reviewers* for Starting and Consolidator Grant

calls, plus source-checked notes on scoring scales, proposal

structure, eligibility windows, panel structure, and the ERC's

AI-use rules. The prompt loads the rubric, applies structural caps

that fire when an expected element is missing, and produces an

evidence-grounded critique.



This package is the ERC-specific application of two general

research-audit projects by the same author group:

[`tjhavranek/research-audit-duel-protocol`](https://github.com/tjhavranek/research-audit-duel-protocol)

(manual multi-model adversarial-debate protocols) and

[`tjhavranek/mad-research`](https://github.com/tjhavranek/mad-research)

(Claude Code skills that automate the same audit discipline for

Claude + Codex). The Advanced pre-review here is a direct

extension of the latter; the multi-model convergence walkthrough

in [`docs/multi_model_walkthrough.md`](docs/multi_model_walkthrough.md)

is a direct application of the former.



A sibling project,

[`tjhavranek/paper-workshop`](https://github.com/tjhavranek/paper-workshop),

is a heavier Claude Code skill that runs an adversarial expert

workshop on a full manuscript and then rebuilds it; it is built for

papers but can be adapted to proposals. It is noted here for

completeness rather than recommended for ERC use, because it does

something this pre-review deliberately avoids: it proposes and writes

edits, whereas this package only identifies problems and leaves the

drafting to the applicant. It is not calibrated to the ERC rubric and

is not part of this package.



[![License](https://img.shields.io/badge/license-MIT-green)](LICENSE)

[![DOI](https://zenodo.org/badge/1251103176.svg)](https://doi.org/10.5281/zenodo.20829165)



## Use



1. Open a paid chat session with a current frontier model. Confirm

   training opt-out is on. (Provider settings change; see Privacy

   below.)

2. Copy the text between the `=== PROMPT BEGIN ===` and `=== PROMPT

   END ===` markers in [`basic/prompt.md`](basic/prompt.md). Paste

   it into the chat.

3. Paste your current draft after the prompt. State which stage you

   are at:

   - **Pitch** — idea sketch, or abstract plus draft CV.

   - **Part I + CV** — Extended Synopsis (Part I of the Scientific

     Proposal) in progress, with a draft CV.

   - **Full proposal** — complete B1 (cover-page abstract, Part I,

     CV and track record), plus any available B2 draft (Part II;

     required for final ERC submission).

4. Read the output. The model returns the top findings ranked by

   severity, each grounded in a verbatim quote from your draft;

   which structural caps fired; a short list of what the next draft

   stage needs to add; and a paragraph you can attach when sending

   the draft to a workshop reader.



## Privacy



Use a paid tier with training opt-out enabled, or remove names and

institutions before pasting a proposal draft into any chat product.

Provider UI labels change every few months, so check the provider's

current data-controls page rather than relying on setting names

copied here:

[ChatGPT data controls](https://help.openai.com/en/articles/7730893-chatgpt-privacy-practices),

[Anthropic Claude privacy](https://privacy.claude.com/en/articles/10023580-is-my-data-used-for-model-training),

and [Gemini activity and privacy](https://support.google.com/gemini/answer/13594961).

Pasting an unpublished draft into any chat product carries residual

risk even when training is off. If the proposal contains embargoed,

patent-sensitive, or otherwise non-public material, sanitise it or

do not use the tool. If someone other than the applicant runs the

pre-review, follow the consent rule in

[`docs/for_workshop_leaders.md`](docs/for_workshop_leaders.md).



## Limitations



The tool is calibrated for ERC Starting and Consolidator Grants

only — not Advanced, Synergy, Proof of Concept, or ERC Plus. It

is in English; the ERC working language of evaluation is English.

It catches routine structural problems and does not judge novelty

in a specific field, panel strategy, or interview credibility —

these remain workshop, mentor, and research-office work. Frontier

models confidently miss field-specific failure modes; the

applicant should push back on findings they disagree with on

merit.



The ERC rubric changes annually. The version in

[`shared/rubric_locked.md`](shared/rubric_locked.md) was last

verified on 2026-05-30 against ERC Work Programme 2026 and the

*Guide for Peer Reviewers* v6.0 (30 September 2025). If you read

this twelve months later, re-verify before use.



## For workshop leaders



If you are running an ERC workshop and want to recommend the tool

to applicants, the operational note at

[`docs/for_workshop_leaders.md`](docs/for_workshop_leaders.md)

covers the hand-off template and the consent rule that applies

when a reader runs the tool on someone else's draft.



## Other ways to use the package



The single-prompt pre-review above is what most applicants will

use. The repository also contains:



- A three-prompt sequence in [`standard/`](standard/) for

  applicants who want a more thorough single-model pass

  (Panel Reviewer, then Devil's Advocate, then Writing Coach).

- A Claude Code + Codex CLI integration in

  [`advanced/`](advanced/) that runs the

  [`mad-research`](https://github.com/tjhavranek/mad-research)

  protocol against the same ERC rubric (experimental; not yet

  end-to-end pilot-verified — see

  [`advanced/README.md`](advanced/README.md)).

- A question-bank and answer stress-test prompt pair in

  [`mock_interview/`](mock_interview/) for Step-2 applicants

  preparing for the panel interview.

- A resubmission audit prompt in [`resubmission/`](resubmission/)

  that checks whether a new draft engages with a previous

  Evaluation Report.



Synthetic test fixtures used to exercise the prompts are in

[`tests/fixtures/`](tests/fixtures/). Roadmap and development

notes are in [`docs/roadmap.md`](docs/roadmap.md).



## Citation, licence, maintainer



Developed by Tomáš Havránek and Zuzana Iršová, Charles University,

Prague. MIT licence; see

[`LICENSE`](LICENSE). The ERC materials cited in the rubric remain

the property of the European Research Council Executive Agency

and are referenced under fair use with source URLs in

[`shared/rubric_locked.md`](shared/rubric_locked.md). Archived on

Zenodo with a DOI that resolves to the latest release:

[`https://doi.org/10.5281/zenodo.20829165`](https://doi.org/10.5281/zenodo.20829165).

For citation metadata see [`CITATION.cff`](CITATION.cff).



Bug reports and factual corrections to the rubric: GitHub Issues.

Please do not paste real proposal content in public issues.

ERC-panel-veteran feedback on the prompt is particularly welcome.



Roadmap and development notes are in

[`docs/roadmap.md`](docs/roadmap.md). The audit history of each

version is in [`CHANGELOG.md`](CHANGELOG.md).