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Ralphinho rfc pipeline

Skill bg-szy/TOP-SKILLS/skills/awesome-skills/ralphinho-rfc-pipeline

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Install
npx -y skills add bg-szy/TOP-SKILLS --skill ralphinho-rfc-pipeline

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

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

RFC-driven multi-agent DAG execution pattern with quality gates, merge queues, and work unit orchestration.

SKILL.md

1.5 KB, 307 tokens by cl100k_base, as published. Nobody here has run it

Ralphinho RFC Pipeline

Inspired by humanplane style RFC decomposition patterns and multi-unit orchestration workflows.

Use this skill when a feature is too large for a single agent pass and must be split into independently verifiable work units.

Pipeline Stages

  1. RFC intake
  2. DAG decomposition
  3. Unit assignment
  4. Unit implementation
  5. Unit validation
  6. Merge queue and integration
  7. Final system verification

Unit Spec Template

Each work unit should include:

  • id
  • depends_on
  • scope
  • acceptance_tests
  • risk_level
  • rollback_plan

Complexity Tiers

  • Tier 1: isolated file edits, deterministic tests
  • Tier 2: multi-file behavior changes, moderate integration risk
  • Tier 3: schema/auth/perf/security changes

Quality Pipeline per Unit

  1. research
  2. implementation plan
  3. implementation
  4. tests
  5. review
  6. merge-ready report

Merge Queue Rules

  • Never merge a unit with unresolved dependency failures.
  • Always rebase unit branches on latest integration branch.
  • Re-run integration tests after each queued merge.

Recovery

If a unit stalls:

  • evict from active queue
  • snapshot findings
  • regenerate narrowed unit scope
  • retry with updated constraints

Outputs

  • RFC execution log
  • unit scorecards
  • dependency graph snapshot
  • integration risk summary

Gives 0 of the 12 instructions most plan spec skills give in 307 tokens

Counted across 1,100 of the 1,860 authors here whose files we hold, read 2026-08-06

  • ask one question at a timein 46 of 1100, across 38 files
  • Break plans into vertical slicesin 28 of 1100, across 10 files
  • Publish issues in dependency orderin 27 of 1100, across 9 files
  • Iterate until user approves the breakdownin 24 of 1100, across 6 files
  • Explore the repository to understand the codebase statein 24 of 1100, across 7 files
  • Use domain glossary vocabularyin 23 of 1100, across 5 files
  • Apply correct triage labels to published issuesin 23 of 1100, across 5 files
  • Write failing tests before implementation codein 23 of 1100, across 18 files
  • Prefer AFK slices over HITLin 22 of 1100, across 7 files
  • ask clarifying questions until requirements are concretein 21 of 1100, across 13 files
  • Respect existing architecture decision recordsin 20 of 1100, across 5 files
  • write a specification before writing any codein 20 of 1100, across 12 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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Skills are one crate of 328,083. 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.