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port-pipeline

Assess and port custom model pipeline implementations to Diffusers: summarize scope and complexity and get user confirmation before implementation, preserve behavior, avoid new dependencies, and keep device/attention handling configurable. Always invoke port-model after the pipeline port to complete remaining SD.Next model integration. Use when migrating custom or non-Diffusers pipeline code into SD.Next repo-local pipeline files such as pipelines/model_<name>.py or pipelines/<model>/pipeline.py.

Quality

87%

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SKILL.md
Quality
Evals
Security

Quality

Content

81%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a well-structured, highly actionable workflow with strong validation gates and feedback loops, and it stays lean by assuming Claude's competence. The main improvement areas are trimming redundant emphasis in step 9 and the checklist, and moving detailed Diffusers convention guidance into reference files.

Suggestions

Trim redundant emphasis in step 9 and the Review Checklist — several items restate constraints already stated in the Constraints and Workflow sections.

Move detailed Diffusers interface/scheduler conventions (step 3 and 5 details) into a reference file and keep a one-line pointer in the workflow to improve progressive disclosure.

Add a short worked example (e.g., a minimal pipeline __init__/__call__ signature or from_pretrained pattern) to lift actionability from mostly-executable to copy-paste ready.

DimensionReasoningScore

Conciseness

Mostly efficient imperative bullets with no explanation of concepts Claude already knows, but step 9 pads its point ('Do not treat this handoff as optional or merely recommend it as a follow-up') and some constraint/checklist items repeat guidance already stated in the workflow. Fits 'efficient with minor instances that could be trimmed' rather than the lean 5.

4 / 5

Actionability

Gives concrete commands ('source venv/bin/activate', 'pnpm ruff', 'ruff check <file> --fix', 'pnpm pylint') and concrete file layouts ('pipelines/<model>/transformer.py', 'scheduler_<name>.py'), and the instruction-only guidance is specific and executable. Falls short of 5 only because implementation steps describe patterns rather than giving a worked signature or snippet for the common case.

4 / 5

Workflow Clarity

A clearly sequenced 10-step workflow with explicit validation checkpoints: the mandatory clarification gate, the scope-and-confirmation gate before implementation, lint with 'Re-run both linters after fixes to confirm a clean result', behavior-parity validation, and a final review checklist — a complete validate/fix/retry feedback loop.

5 / 5

Progressive Disclosure

Well-organized sections (When To Use, Constraints, Workflow, Review Checklist, Output Expectations) in a single file with no bundle files, and the one external pointer ('.github/instructions/core.instructions.md') is clearly signaled and one level deep. Not a 5 because some detailed conventions (e.g., Diffusers scheduler/API patterns) are inlined in workflow steps where reference files would keep the overview leaner.

4 / 5

Total

17

/

20

Passed

Description

88%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description that states concrete capabilities in third person and includes an explicit, concrete 'Use when' trigger clause tied to specific file patterns. The main weaknesses are incomplete synonym coverage and slight scope overlap with the companion port-model skill.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'port custom model pipeline implementations to Diffusers', 'summarize scope and complexity and get user confirmation', 'preserve behavior', 'avoid new dependencies', 'keep device/attention handling configurable', 'invoke port-model' — with comprehensive coverage of the porting workflow.

5 / 5

Completeness

Explicitly answers both 'what' (assess, port, confirm, configure, hand off to port-model) and 'when' with a concrete 'Use when migrating custom or non-Diffusers pipeline code into SD.Next repo-local pipeline files such as pipelines/model_<name>.py or pipelines/<model>/pipeline.py' trigger clause.

5 / 5

Trigger Term Quality

Good natural keyword coverage ('port', 'pipeline', 'Diffusers', 'migrating', 'custom pipeline code', concrete file patterns like 'pipelines/model_<name>.py') but leans technical and misses common variations such as 'convert'. Not a 5 because synonym coverage is incomplete; not a 3 because the terms present are ones users would naturally say for this task.

4 / 5

Distinctiveness Conflict Risk

A clear niche (SD.Next repo-local pipeline ports with specific file paths) with distinct triggers, but the description covers part of the sibling 'port-model' skill's scope ('Always invoke port-model... to complete remaining SD.Next model integration'), creating minor overlap risk with that closely related skill.

4 / 5

Total

18

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

vladmandic/sdnext

Path

.github/skills/port-pipeline/SKILL.md

Reviewed

Table of Contents

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