skills/reference-project-synthesizer/SKILL.md
Connect structured reference source cards to the active ML project. Use when papers, collaborator docs, Markdown notes, specs, scripts, BibTeX files, or source bundles should inform claims, risks, baselines, benchmarks, experiments, algorithm design, implementation, writing contracts, citations, collaborator actions, project initialization, or memory writeback.
npx skillsauth add a-green-hand-jack/ml-research-skills reference-project-synthesizerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Convert source cards into project decisions. This skill answers: What does this source mean for our project?
Use after reference-reading-summarizer has produced a source card. Do not repeatedly re-read raw sources unless the card is insufficient or low confidence.
<installed-skill-dir>/
├── SKILL.md
├── references/
│ └── project-link-routing.md
└── templates/
└── project-use-note.md
Prefer:
reference/cards/<source-id>.mdreference/.agent/source-index.mdreference/.agent/processing-status.mdreference/.agent/reference-index.md and reading-status.mdmemory/current-status.mdmemory/claim-board.mdmemory/evidence-board.mdmemory/risk-board.mdmemory/action-board.mdpaper/.agent/writing-contract.mdcode/.agent/benchmark-plan.md or equivalent, when presentRead references/project-link-routing.md.
reference/project-use/<source-id>.md from templates/project-use-note.md.memory/claim-board.md + memory/evidence-board.mdmemory/risk-board.md + memory/action-board.mddocs/experiments/ or memory/evidence-board.mdmemory/decision-log.mdpaper/.agent/writing-memory/ via paper-writing-memory-managermemory/risk-board.md or paper/.agent/paper-evidence-board.mdmemory/provenance-board.mdreference-reading-summarizer with the required reading mode.Each project-use note should include:
End with the closure audit:
Goal: What project question did this source help answer?
Answer: What did we learn?
Path: Which card, sections/files, and memory objects support this?
Correctness: Why should we trust it, and what needs deeper reading?
Next: What changes in the project?
testing
Bootstrap project-local ml-research-skills. Use from global installs when creating a new ML research project, enabling this collection in an existing ML research repo, or deciding whether to install the full bundle locally. Route to project-init for new projects; do not handle paper or experiment work directly.
development
Route project operations tasks — git, memory, bootstrap, remote, workspace, code review, timeline, ops — to the correct skill. Use when the task involves commits, pushes, worktrees, project memory, enabling project-local skills, SSH/server coordination, sidecar runners, or audits. Do not solve the ops task directly.
testing
Route ML/AI paper writing tasks to the correct skill — contract planning, prose drafting, section writing, consistency editing, review simulation, rebuttal, submission, or citation work. Use when the task involves writing, revising, reviewing, or submitting a paper instead of guessing between paper-writing-assistant, paper-writing-contract-planner, paper-reviewer-simulator, auto-paper-improvement-loop, or citation skills. Do not draft prose directly.
data-ai
Project-local router for ML research skill selection. Use inside an initialized ML research project, or while maintaining this skill repo, when the user describes an ML research/paper/experiment/discovery/ops/release workflow and may not know the skill; route to a domain router or high-signal leaf. Do not use for generic non-ML projects.