shipkit-engineering-goals

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Derive technical performance criteria from the engineering blueprint. Writes goals/engineering.json with response times, reliability, coverage thresholds. Evaluate mode checks actuals against targets.

AI & Automation 1 stars 0 forks Updated 1 weeks ago MIT

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Skill Content

# shipkit-engineering-goals — Technical Performance Criteria **Purpose**: Derive measurable technical performance criteria from the engineering blueprint. Each mechanism, component, and design decision implies criteria for "how do we know this performs?" — this skill makes those criteria explicit, measurable, and trackable. **What it does**: Reads the engineering blueprint + stage context, derives technical criteria from cited signals, writes the engineering goal file, and adds engineering criteria to existing stage gates. Most criteria are grounded from `engineering-definition.json`, `stack.json`, and stage — only hard performance targets with no signal become questions. **Protocol:** This skill follows the canonical elicitation protocol defined in `install/shared/references/elicitation-protocol.md` (the *mechanics* — marker, state files, resume). **Calibration:** Apply `install/shared/references/ground-or-ask-calibration.md` (the *intelligence* — propose vs ask). **Ground first:** this is a DERIVATION skill — most criteria flow directly from `engineering-definition.json` (mechanisms → performance/quality/reliability targets), `stack.json` (stack norms), `goals/strategic.json` (stage gates), and `goals/product.json` (outcome alignment). Cite the signal for every proposed threshold and tag it with its source. Flag low-leverage guesses (`guessed: true`). The only HIGH-LEVERAGE ungrounded fields are hard performance/reliability TARGETS where no signal (stage, stack norms, p...

Details

Author
stefan-stepzero
Repository
stefan-stepzero/shipkit
Created
7 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

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