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Rt submission readiness

Skill brycewang-stanford/Awesome-Journal-Skills/Research-Toolkit-Skills/skills/rt-submission-readiness

Use when an author is one revision away from submission and needs a venue-parameterized go/no-go scorecard on the actual manuscript: fit, identification, robustness, exhibits, exposition, venue mechanics, data/code, and pre-empted objections. Returns PASS/FLAG/FAIL per dimension, the blocking gaps, and the desk-reject risk. Reads the venue bar from the target pack + source-map.From its SKILL.md

Install
npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill rt-submission-readiness

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

3.9 KB, 858 tokens by cl100k_base, as published. Nobody here has run it

Submission-Readiness Self-Check (rt-submission-readiness)

The mechanical/structural go/no-go that catches avoidable desk rejects before you hit submit. Full rubric: shared-resources/submission-readiness/readiness-checklist.md. It is the outward-facing analogue of the repo's internal tools/quality_scorecard.py.

When to trigger

  • The draft is "done" and the author is about to submit to a named venue.
  • Before paying a submission fee / starting the portal.
  • After rt-journal-match selects the target and after rt-execution-bridge has run any empirical checks the paper depends on.

Inputs to load

  1. The manuscript or submission packet, including front matter, main text, exhibits, appendix, data/code statement, and cover letter if drafted.
  2. The target journal pack's README.md, relevant skills, and resources/official-source-map.md.
  3. Any executed analysis artifacts from rt-execution-bridge: result handles, audit gaps, robustness outputs, and replication/package notes.

What it does

Reads the target pack's skills + resources/official-source-map.md, inspects the actual manuscript (cite §/table for every flag), and scores nine dimensions PASS / FLAG / FAIL:

  1. Fit & general interest · 2. Contribution clarity · 3. Identification / method ·
  2. Robustness & inference · 5. Exhibits self-contained · 6. Exposition (magnitude up front) · 7. Venue mechanics (page limit / anonymization / fee / cover letter) · 8. Data & code / reproducibility · 9. Pre-empted referee objections.

Go/no-go: any FAIL on Fit, Identification, or Venue-mechanics is a no-go (the classic desk-reject triggers).

Decision contract

ResultMeaningRequired next action
GONo blocking FAIL and all venue mechanics are verified.Run rt-simulated-referee for the substantive attack surface before submission.
CONDITIONAL GONo fatal desk-reject trigger, but one or more FLAG items will draw reviewer pressure.Fix or explicitly justify each FLAG; rerun this check on the changed sections.
NO-GOAny FAIL on fit, identification/method, or venue mechanics, or an unverifiable required venue rule.Route each blocking item to the owning target-pack skill and rerun before opening the portal.

For UNKNOWN, name the missing evidence and the smallest artifact needed to resolve it. Do not silently upgrade UNKNOWN to PASS.

Hard rules

  1. Read the manuscript; cite locations — no status without a §/table/page reference.
  2. Venue facts live from the source-map, never from memory.
  3. No false green — unverifiable dimension → UNKNOWN, not PASS.
  4. Map every FAIL/FLAG to the owning skill (and its execution bridge) so the author knows exactly where to fix it.
  5. Separate mechanics from judgment — this skill catches preventable desk-reject risk; use rt-simulated-referee for the substantive probability of surviving peer review.

Output format

【Venue】… (bar: pack skills + source-map, read live)
【Scorecard】1 Fit … PASS/FLAG/FAIL — note (§ cited) · … (dims 2–9)
【Go / No-go】GO / NO-GO — deciding dimension(s)
【Blocking gaps (FAIL)】ranked; each with the fix + owning skill
【Will-be-pushed (FLAG)】referee-anticipation list
【Unknowns】missing evidence required before a green light
【Desk-reject risk】low / medium / high — why

Next: if readiness passes, rt-simulated-referee for the substantive adversarial review.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.