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deployment-guide

Complete deployment guide for Dr. Sophia AI on Railway. Covers environment-aware build system, frontend dist/ compilation, backend auto-deploy, Railway configuration, troubleshooting build/deployment issues. Use when deploying to Railway, building frontend for production, debugging deployment failures, or setting up environment variables.

Quality

84%

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SKILL.md
Quality
Evals
Security

Quality

Content

77%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 highly actionable with clear, validated workflows for both frontend and backend deployment, but it is held back by redundancy (the dist/-build requirement repeated across five sections), inlined time-sensitive details, and a references section where two of three linked files are missing.

Suggestions

Create the missing references/build-troubleshooting.md and references/railway-config.md (or remove their links) so the 'Detailed Documentation' section resolves to real files.

State the critical 'build dist/ and commit it' fact once and let the checklist, failure table, and footer reference it, cutting the current repetition across five sections.

Move volatile details (environment URL table, Railway dashboard links, version numbers, 'Last Updated' date) into the reference files or a clearly marked section so they don't clutter the core workflow.

DimensionReasoningScore

Conciseness

Mostly efficient commands and tables, but the core 'must build dist/' fact is restated in the critical-fact callout, the frontend steps, the checklist, the failure table, and the footer, and time-sensitive details ('Last Updated: September 21, 2025', '~55KB', '~450KB', 'v13.2.7') are inlined rather than isolated in a deprecated section. Not the padded over-explanation of 2, but the repetition and time-sensitive inlining exceed the 'minor instances' of 4.

3 / 5

Actionability

Fully executable, copy-paste-ready guidance throughout: 'cd frontend; npm run build', 'ls -lh dist/assets/*.css', the git add/commit/push flow, 'curl .../health | jq .version', and the verify-deployment.sh invocation with expected output cover the common cases.

5 / 5

Workflow Clarity

Clear sequenced frontend and backend processes with explicit checkpoints ('Step 3: Verify Build' with file-size assertions, post-deploy verification, version-match check), plus checklists and an issue→cause→fix table providing error-recovery feedback loops.

5 / 5

Progressive Disclosure

The 'Detailed Documentation' section is clearly signaled, but 2 of its 3 links (references/build-troubleshooting.md and references/railway-config.md) point to files that do not exist, so navigation breaks; the body also inlines detail (environment URL table, Railway dashboard links) that belongs in the referenced files. Better organized than the monolithic/unsignaled level of 2, but the broken references and inline detail prevent a 4.

3 / 5

Total

16

/

20

Passed

Description

87%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: it states concrete capabilities, includes an explicit 'Use when...' clause with natural trigger phrases, and occupies a distinct niche. The only weaknesses are noun-phrase coverage rather than active verbs and a few missing trigger variations.

DimensionReasoningScore

Specificity

Names several concrete capability areas ('environment-aware build system, frontend dist/ compilation, backend auto-deploy, Railway configuration, troubleshooting build/deployment issues'), but these are coverage-area noun phrases rather than the multiple explicit actions of a top score; minor gaps keep it below 5 and it is clearly above the 1-2-action level of 3.

4 / 5

Completeness

Explicitly answers both what ('Complete deployment guide for Dr. Sophia AI on Railway. Covers environment-aware build system...') and when ('Use when deploying to Railway, building frontend for production, debugging deployment failures, or setting up environment variables') with concrete trigger phrases, matching the top anchor exactly.

5 / 5

Trigger Term Quality

Good natural phrases users would actually say ('deploying to Railway', 'building frontend for production', 'debugging deployment failures', 'setting up environment variables'), but a few common variations are missing (e.g. 'dist', 'build issues', 'npm run build'), so it is not the comprehensive synonym coverage of 5.

4 / 5

Distinctiveness Conflict Risk

A clear niche ('Dr. Sophia AI on Railway') with distinct triggers ('deploying to Railway', 'frontend for production') means minimal risk of triggering the wrong skill; no overlap with generic deployment skills.

5 / 5

Total

18

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 2 missing

Warning

referenced_paths_exist

Referenced path issues: 4 missing

Warning

Total

14

/

16

Passed

Repository

fernandezbaptiste/Skrillz

Path

skill-builder-package/examples/deployment-guide/SKILL.md

Reviewed

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