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Design the idiomatic Elixir architecture for a rewrite: set the compatibility bar (ADR-000), consult phx specialists on open questions, then build contexts, ledger and ADRs. Use after /rewrite:analyze.

oliver-kriska/claude-elixir-phoenix Claude Code author: oliver-kriska 3 files · 1 script body ≈ 1 775 tokens Open the sourcegithub.com↗ analyzed 5 h ago

Design the idiomatic Elixir architecture for a rewrite: set the compatibility bar (ADR-000), consult phx specialists on open questions, then build contexts…

As a process C 62/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentAI and agentsOperations and projectstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
C
62/100
Has gaps
Result and completion w 14
0
When it triggers w 12
20
Inputs and preconditions w 11
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "effort"
    • note edit-residue the text marks something as outdated (lines 55, 74, 76, 78, 115): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 62/100

    • 0Result and completion. Does not say what the result is
    • 20When it triggers. No condition that starts the skill
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 100Steps. 15 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1775 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 201: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 15 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.