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Sprint projectSep 14, 2026hangzhou

AI Incident Relay

Clare Yang · Team C-Star AI Hub

Submitted to AI Incident Response Sprint. Sprint projects are early-stage work by participants, not Apart Research publications.

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Report: AI Incident Relay

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An Evidence-Constrained Codex Skill for Source-Grounded AI Incident Research

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How much would this matter for AI safety if it worked? How innovative is it? For scores of 4-5: is this actually new to the field, or replicating recent work?

Scoring guide
  1. 1Negligible. No clear problem addressed, or no meaningful novelty.
  2. 2Limited. Addresses a real problem but with a generic or well-trodden approach. Incremental at best.
  3. 3Moderate. Clear problem with a reasonable approach; some novelty in framing or method beyond routine application of existing tools.
  4. 4Significant. Important problem with an original approach, or identifies a neglected problem area. A valuable contribution others could build on.
  5. 5Exceptional. Tackles a critical AI safety problem with a genuinely novel approach, or opens a new research direction. Clear theory of change. You'd be excited to share this with researchers in the area.

How sound are methodology, implementation, and findings?

Scoring guide
  1. 1Seriously flawed. Methodology broken, results uninterpretable, or implementation doesn't work.
  2. 2Weak. Approach has significant gaps: missing validation, flawed experimental design, or incomplete implementation.
  3. 3Competent. Technically solid given the short duration. Methodology makes sense, results are interpretable, limitations acknowledged, work builds toward clear conclusions.
  4. 4Strong. Thorough methodology with convincing validation. Results clearly support conclusions. Immediately useful for future work.
  5. 5Exceptional. Ambitious scope executed rigorously. Surprising findings, novel methods, or unusually robust validation.

How clearly are work, findings, and impact potential communicated?

Scoring guide
  1. 1Incomprehensible. Cannot determine what the project is actually claiming or doing.
  2. 2Hard to follow. Key information buried, missing, or diluted by excessive length. Significant effort to extract main points.
  3. 3Clear enough. Can understand the problem, approach, and results without undue effort. Core content clearly present: problem, method, findings, limitations.
  4. 4Well presented. Easy to follow, well-structured, appropriate level of detail. Target audience would get it quickly.
  5. 5Exceptionally clear. A pleasure to read. Complex ideas made accessible. Could serve as a model for how to present this type of work.
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  1. This project is well-thought-out, but I think the problem it addresses is more interesting to journalists or communications people than it is to an AI safety researcher. It's possible I'm wrong though, so I'd like to see proposed use cases to help the reader understand the target audience.

  2. This is a well-motivated and well-scoped prototype. The ledger design is sensible, but the methods would be clearer if each separation were linked to the specific failure it prevents (e.g., whether the agent rejects a summary that presents an organisation's claim as established fact, or that counts derivative reports as independent corroboration).

Cite this project

@misc{yang2026ai,
  title = {{AI Incident Relay}},
  author = {Clare Yang},
  year = {2026},
  month = sep,
  note = {Submitted to AI Incident Response Sprint, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/ai-incident-relay-osv1}},
  url = {https://apartresearch.com/sprints/projects/ai-incident-relay-osv1}
}

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