用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/Morrison-Lab/ai-config --skill promote-memory命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | promote-memory |
| description | Promote project memory to shared. |
| user-invocable | true |
| allowed-tools | ["Bash","Read","Edit","Write"] |
Work through learn's staging file
(learn-staging.md) and decide, entry by entry, whether each candidate is
durable enough to promote into committed memory. This is a single-pass
review, not a multi-agent council — see "Why single-pass, not a critic
panel" below for why that's the right weight here.
ums pass, once learn-staging.md has
accumulated entries since the last reviewlearn-staging.md is getting long enough that an unreviewed pile is
itself a problem (nothing lost, but nothing promoted either)A five-critic-council review (independent votes on generality, staleness, redundancy, evidence, and format, then a majority/consensus call) is one way to run this gate, and is what some other agent-workflow setups use. For this repo's scale — a single maintainer's personal skill corpus, reviewed by the same agent that staged the entries in the first place — that's more process than the problem needs: there's no multi-party disagreement to adjudicate, and the criteria below are checkable in one pass without a panel to catch a single reviewer's blind spot. This skill runs one pass through explicit, named criteria instead. Revisit this if the staging file starts accumulating contested entries a single pass keeps getting wrong — that would be the signal a heavier review is actually earning its cost.
~/.claude/projects/<project-slug>/memory/learn-staging.md. If it's empty
or missing, say so and stop — nothing to promote.
For every staged entry, check:
CLAUDE.md/memories/*.md entry
already say this? Grep the likely destination file first. If it's a
near-duplicate, either skip it or fold in anything the existing entry
lacks rather than adding a second copy.record-learnings' own routing table
(user-wide /memories/, repo-specific project memory, a shared skill, or
CLAUDE.md) and its same conventions (check existing notes first, bullet
form, the why not just the what, register a new /memories/ file in
MEMORY.md).learn-staging.md. Too narrow,
contradicted, or already covered elsewhere. No need to explain a discard
at length; one line is enough if a rationale is worth keeping at all.learn-staging.md for now (e.g. evidence is thin
but the claim seems plausible and worth re-checking next time, or it
needs a decision only the user can make). Don't let holds accumulate
silently forever — if the same entry survives several reviews unresolved,
surface it explicitly and ask.Remove every entry that was promoted or discarded from learn-staging.md,
leaving only holds. Report a short summary: how many promoted (and where),
how many discarded (and why, briefly), how many held.
learn — the staging half this skill reviews. See its own doc for
why staging exists at all.record-learnings / memorize — this skill promotes into the
same destinations and follows the same routing/format conventions
record-learnings already documents; it doesn't reinvent them.ums — a natural point to fold a promote-memory pass in, since both
run periodically over accumulated session learnings. Running
promote-memory doesn't require ums though; it can run standalone
whenever staging needs clearing.