Recall behavioral decision content with trigger, section, or file modes.
npx skills add https://github.com/ddaanet/edify-plugin --skill when
Please help me install this Agent Skill. Skill: when Source: https://github.com/ddaanet/edify-plugin/tree/main/skills/when Command: npx skills add https://github.com/ddaanet/edify-plugin --skill when
Teams often lose track of context from prior decisions, leading to debates and inconsistent actions. This skill helps recall behavioral knowledge from project decisions to inform current work.
Invoke with /when <trigger> to recall a behavioral decision from memory.
High-intent search queries and answers about installing and using this skill.
To recall past project decisions, you can retrieve behavioral knowledge on demand using trigger-mode to locate specific guidance and return the decision content with linked navigation.
Retrieving context from prior decisions during code review is best handled by applying section-mode or file-mode to locate relevant behavioral guidance and return the decision content.
You can navigate related project decisions by using the linked navigation feature, which connects retrieved behavioral knowledge to provide quick access across related decision content.
Yes, you can use trigger-mode to locate behavioral knowledge for project onboarding, applying it to quickly recall specific guidance and return the relevant decision content.
You need deterministic recall for project memory management when teams lose track of context from prior decisions, leading to inconsistent actions and requiring precise guidance retrieval.
Yes, this decision recall approach supports context-rich retrieval by offering trigger-mode, section-mode, and file-mode to locate guidance and return decision content with navigation.
epieczkoLog Betty Framework skill executions as timestamped JSON audit entries.
ev3rlitSummarize project progress and context across multiple repositories.
chapzinQuery and update the local LLM wiki for durable project memory.
AribSudiaSearch project memory files for historical decisions using semantic and lexical methods.
