Convert recurring knowledge into codified project rules under .agents/rules.
npx skills add https://github.com/ericklemos/ai-tools --skill archivist-ericklemos
Please help me install this Agent Skill. Skill: archivist Source: https://github.com/ericklemos/ai-tools/tree/main/.agents/skills/archivist Command: npx skills add https://github.com/ericklemos/ai-tools --skill archivist-ericklemos
Recurrent knowledge and proven patterns often remain implicit, causing teams to reinvent solutions and lose context.
Transform a known recurring pattern into a formal rule to capture it for future use.
High-intent search queries and answers about installing and using this skill.
You can codify undocumented patterns into actionable project rules by storing them under the .agents/rules directory. This prevents repeat mistakes and accelerates team onboarding by preserving proven decisions.
The best way to retain implicit engineering knowledge is codifying proven patterns into durable project rules. This achieves cross-agent knowledge alignment and preserves decisions to stop teams from reinventing solutions.
To set up project automation, create a SKILL.md file with YAML frontmatter containing a name and description. You can optionally add scripts, references, and assets directories to support the codified rules.
Codifying project rules enables cross-agent knowledge alignment by converting recurring knowledge into actionable constraints. All agents operate under the same patterns stored in the shared .agents/rules directory.
Avoid codifying team workflows into project rules when the knowledge is not recurrent or proven. Codifying one-off solutions or non-recurring context adds unnecessary constraints without providing durable project value.
ak110Align team coding quality and testing across projects with a common baseline.
HMWKRScan git changes and commit history to detect unrecorded technical insights.
daffy0208Conduct structured user research through interviews and surveys to create personas and journey maps.
tyevansOrchestrate curation, promotion, and demotion of agent learnings and project rules.
