Topic proposals and voting

Proposals and voting are closed. Proposal P-01 was selected on 2026-09-14 (ADR-0004), while the project was briefly solo (ADR-0005). The four-person group was reinstated on 2026-09-15 (ADR-0006), and P-01 remains selected. Any member may open a Decision needed issue to revisit the topic before Sprint 1 planning on Thu 2026-09-17. The ranked-ballot vote stays retired. The rest of this page is kept as the record of the original process.

Selected proposal

ID	Proposer	Title	Dataset	Based on rubric question	Document	Issue	Status
P-01	Jerad Dunne	Risky capabilities in copied agent skills: prevalence, reach, and drift	GitSkills	4 (security and supply chain) with 1 (reuse and propagation)	P-01	#41	Selected 2026-09-14

Fallback topic if P-01 proves infeasible in Sprint 1: rubric question 2 (skill quality indicators), reusing the scanner output as features.

Original process (retired)

The sections below describe the group process planned on 2026-09-13 (ADR-0002, superseded by ADR-0005).

Timeline (as planned)

Step	Deadline	Who
Read 00-candidate-questions.md and the dataset READMEs	2026-09-13 to 09-14	everyone
Submit proposals via the Project proposal issue form (at least one each)	2026-09-14 23:59	everyone
Read every proposal; ask clarifying questions as issue comments	2026-09-15	everyone
Cast a ballot (PR adding votes/ballots/<handle>.yml)	2026-09-15 23:59	everyone
Tally (make tally), confirm at kickoff, write ADR-0004, fill RESEARCH_QUESTION.md	2026-09-16	Scrum Master, Product Owner

How proposals were to be written

1. Open Issues > New issue > Project proposal. The form asks for the precise research question, unit of analysis, tables and columns, the rubric's required implementation component and minimum evidence, feasibility, risks, and four self-scores.
2. Prefer questions the sample data can answer. The full GitSkills dataset is 41 GB; using it is a decision, not a default.
3. A proposal can refine a rubric question or combine two, but must still meet the rubric's "Required implementation component" for its base question.
4. TEMPLATE-proposal.md is an offline drafting template.

How the vote was to work

• Ballot: each voter ranks acceptable proposals (best first) and scores each on five weighted criteria from 1 to 5 (weights in project.yml under proposals.criteria): feasibility 0.30, data_fit 0.20, rubric_fit 0.20, interest 0.15, low_risk 0.15.
• Winner: instant runoff on the rankings; ties broken by the weighted-criteria score, then by Borda count.
• Transparency: python scripts/tally_votes.py computes the result and writes RESULTS.md. The code remains tested in tests/test_voting.py.

Files

File	Purpose
00-candidate-questions.md	The 15 rubric questions summarized with data-fit and feasibility notes
P-01-jerad-dunne-skill-risk-propagation.md	The selected proposal
TEMPLATE-proposal.md	Offline drafting template (retired process)
votes/README.md, votes/TEMPLATE-ballot.yml	Ballot instructions and format (retired)
votes/ballots/	Ballot folder (unused)
RESULTS.md	Output of scripts/tally_votes.py (no ballots were cast)