.claude/skills/ym-campaign-retro-nextRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
对一次活动做复盘:目标与结果对照、关键节点数据、做得好与失败原因,并给出下一轮可验证的实验假设与衡量指标。当用户说「活动复盘」「这次活动怎么样」「下次怎么改」时使用。 也适用于「活动总结」「活动效果」「campaign retro」这类说法。
These states come from the source or distribution context. None of the entries below are SkillVetAI compatibility test results.
These checks parse the fixed package against dated platform rules. They do not execute the Skill or verify task behavior.
.claude/skills/ym-campaign-retro-nextRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
.agents/skills/ym-campaign-retro-nextRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
skills/ym-campaign-retro-nextRuntime, accounts, dependencies, permissions, network behavior and task quality remain untested.
This command is recorded from the source ecosystem and resolves the registry's latest release. The fixed release shown on this page should be inspected before adoption.
clawhub install @liuyuming0823/ym-campaign-retro-nextclawhub inspect @liuyuming0823/ym-campaign-retro-next --version 0.1.0This automated, non-executing scan is bound to this release hash. It is not a safety certification and may contain false positives or false negatives.
This is registry-supplied evidence for the recorded release, not an independent SkillVetAI scan. Check the canonical source for the full report, scanner versions, scope, and current moderation state.
The catalog stores hashes and an inventory summary for change detection. It does not republish the package contents.
sha256:2b6347ad01b9ec95ae7312db10422e90c1f50f9a5eaa17b811d99440008c55fcreferences/attribution-rules.mdreferences/experiment-template.mdSKILL.mdtemplates/retro-template.md- Initial release of ym-campaign-retro-next. - Provides a structured workflow for campaign retrospectives: compares goals with actuals, identifies key actions, attributes successes/failures (with evidence standards), and suggests three testable experiments for the next round. - Handles incomplete inputs robustly; clearly marks missing goals or data, distinguishing between confirmed data and assumptions. - Output is always in Markdown format, following a fixed multi-section template (goals table, timeline, good/bad points, future experiments, applicability, data gaps). - No external dependencies; relies entirely on user-provided data.