Shaping & Breadboarding

Shape Up methodology for product and feature development. Use when collaboratively shaping a solution — iterating on problem definition (requirements) and solution options (shapes), breadboarding systems into affordances and wiring, and slicing into vertical implementation increments. Triggers include "shape this feature", "breadboard the system", "let's shape", "slice this into increments", "fit check", "define requirements", or any product/feature scoping discussion using Shape Up methodology.

This skill is a plain methodology pack — there are no installs or credentials requested and its content matches the Shape Up/breadboarding purpose. Things to consider before installing or using it: (1) the instructions insist on including verbatim source material and full tables without summarization — avoid pasting secrets, credentials, or sensitive logs into sessions you'll feed to the skill; (2) the guidance suggests creating files (spike-*.md, shaping docs). If your agent runtime can write files, be aware those files may persist in the agent workspace; check workspace permissions and clean up any sensitive artifacts; (3) the strict 'show full tables / never summarize' rule can lead to very large outputs that might inadvertently include private data — review outputs before sharing externally; (4) if you are concerned about autonomous runs, consider keeping the skill user-invocable only (it already is) or disabling autonomous invocation at the agent/platform level. Overall the package is internally coherent and appropriate for its stated purpose.

Type: OpenClaw Skill Name: shaping Version: 1.0.0 The skill bundle provides detailed instructions and references for an AI agent to apply the 'Shape Up' methodology for product and feature development. All files (`_meta.json`, `SKILL.md`, `references/breadboarding.md`, `references/shaping.md`) contain only descriptive text, structured formats, and procedural guidance relevant to the stated purpose. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, or prompt injection attempts designed to subvert the agent for harmful objectives. The instructions focus on guiding the agent's output and thought process within the defined methodology.