Skill
design
Design phase entry. Aggregates plan-level selection, task breakdown, and package output rules; loads references/assets/scripts on demand.
@evidentloopView SkillDevelopment
Skill
/analyze
Analyze phase entry. Aggregates scoring, follow-up, and scope-check rules; loads references/assets/scripts on demand.
Install
$ npx -y skills add evidentloop/sopify --skill analyze --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/analyze
Context preview
The summary Claude sees to decide when to auto-load this skill.
Analyze phase entry. Aggregates scoring, follow-up, and scope-check rules; loads references/assets/scripts on demand.
SKILL.md
analyze.SKILL.mdname: analyze
description: Analyze phase entry. Aggregates scoring, follow-up, and scope-check rules; loads references/assets/scripts on demand.
Analyze (Entry)
> Read the evidence first, then separate the objective, deliverable, and candidate path.
When to activate
- Entering the analysis phase (`workflow` / `plan_only`).
- Need requirement scoring, clarification, or complexity routing.
Execution skeleton
1. Load `references/analyze-rules.md` first. 2. Read user-supplied material and relevant code, separate the objective, deliverable, and candidate path, then score completeness. 3. If the score is below threshold, follow `auto_decide`:
- `false`: ask follow-up questions with `assets/question-output.md`.
- `true`: state explicit assumptions, then continue.
4. After the score passes, hand off confirmed success criteria, scope, evidence, and unknowns that could still affect the result. 5. Render the phase summary with `assets/success-output.md`.
Resource navigation
- Long rules: `references/analyze-rules.md`
- Shared writing standards: `../references/shared-writing-dna.md` (apply to all output)
- Output contract: `../references/output-contract.md` (required sections, conditional enhancement, self-check)
- Follow-up template: `assets/question-output.md`
- Success template: `assets/success-output.md`
- Deterministic scoring script: `scripts/score_requirement.py`
Deterministic logic first
Use the script when the score must be auditable:
python3 skills/en/skills/sopify/analyze/scripts/score_requirement.py \
--goal-clarity 2 \
--expected-outcome 2 \
--scope-boundary 1 \
--constraints 1 \
--require-score 7
The script returns JSON with total score, threshold result, and missing dimensions.
Boundaries
- This skill does not generate a plan package directly; hand off to `design`.
- This skill does not execute code changes directly; hand off to `develop`.
Read more
name: analyze description: Analyze phase entry. Aggregates scoring, follow-up, and scope-check rules; loads references/assets/scripts on demand.
Analyze (Entry)
> Read the evidence first, then separate the objective, deliverable, and candidate path.
When to activate
- Entering the analysis phase (`workflow` / `plan_only`).
- Need requirement scoring, clarification, or complexity routing.
Execution skeleton
1. Load `references/analyze-rules.md` first. 2. Read user-supplied material and relevant code, separate the objective, deliverable, and candidate path, then score completeness. 3. If the score is below threshold, follow `auto_decide`:
- `false`: ask follow-up questions with `assets/question-output.md`.
- `true`: state explicit assumptions, then continue.
4. After the score passes, hand off confirmed success criteria, scope, evidence, and unknowns that could still affect the result. 5. Render the phase summary with `assets/success-output.md`.
Resource navigation
- Long rules: `references/analyze-rules.md`
- Shared writing standards: `../references/shared-writing-dna.md` (apply to all output)
- Output contract: `../references/output-contract.md` (required sections, conditional enhancement, self-check)
- Follow-up template: `assets/question-output.md`
- Success template: `assets/success-output.md`
- Deterministic scoring script: `scripts/score_requirement.py`
Deterministic logic first
Use the script when the score must be auditable:
python3 skills/en/skills/sopify/analyze/scripts/score_requirement.py \ --goal-clarity 2 \ --expected-outcome 2 \ --scope-boundary 1 \ --constraints 1 \ --require-score 7
The script returns JSON with total score, threshold result, and missing dimensions.
Boundaries
- This skill does not generate a plan package directly; hand off to `design`.
- This skill does not execute code changes directly; hand off to `develop`.
Ships withsopify
Resumable AI coding — ask first, plans stay with the repo AI coding tools are fast. But when they jump to code before the facts are clear, speed turns into rework.
Get the whole plugin
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