lore-compact

lore-compact is a skill for Claude Code, Codex from koersliven/Lore. It costs 20 tokens per session (931 once invoked), scanned A, original, Apache-2.0.

A context-cleanup skill that merges, removes duplicates from, and summarizes stored knowledge entries while keeping their sources for later tracing.

In plain words
What is it for?
It helps maintain project context by grouping related decisions, preserving conflicts, and updating detailed and summarized records.
Why use it?
Long knowledge buffers can make saved context bloated and harder to use. It keeps the current snapshot concise without discarding the original records.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/koersliven/lore/lore-compact
Any agent
npx skills add koersliven/Lore --skill lore-compact
Clone the repo
git clone --depth 1 https://github.com/koersliven/Lore

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for lore-compact

README.md
[![agentmods](https://agentmods.dev/badge/skills/koersliven/lore/lore-compact.svg)](https://agentmods.dev/skills/koersliven/lore/lore-compact)
Your own site
<a href="https://agentmods.dev/skills/koersliven/lore/lore-compact"><img src="https://agentmods.dev/badge/skills/koersliven/lore/lore-compact.svg" alt="Measured on agentmods" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 931 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00020 $0.00931
Opus 5 $0.00010 $0.00465
Sonnet 5 $0.00004 $0.00186
Haiku 4.5 $0.00002 $0.00093

Measured 4d ago against content hash 514c956a18e1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lore-compact scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/lore-compact/SKILL.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/compact — Knowledge Window Compression

类比 Claude Code 的上下文 compaction,在知识窗口过大时自动压缩,保持 snapshot 精炼。

When to Trigger

  • Stop hook detects buffer has reached compact threshold (8+ entries)
  • User explicitly invokes this skill
  • Before /digest when buffer has 5+ entries (optional optimization)

Purpose

将 buffer 中的多条原始知识压缩为精炼的摘要,减少 snapshot 膨胀,同时保留完整追溯。

核心思想:不是简单 flush,而是先"消化"——合并同类、去除冗余、提取本质。

Process

Step 1: Read Buffer

读取 .ai-context/buffer.md 中的所有原始知识条目。

Step 2: Group by Theme

按主题分组。判断标准:

  • 涉及同一文件 → 同组
  • 涉及同一概念(如"超时"、"缓存") → 同组
  • 同一类型的知识(多个 DECISION 关于同一设计) → 同组

Step 3: Merge and Dedupe

对每组执行:

合并规则

  • 多条关于同一文件的 DECISION → 合并为一条,保留最新原因
  • 多条关于同一约束的重复描述 → 保留最完整的一条
  • 互相矛盾的条目 → 标记 [CONFLICT],保留双方

去重规则

  • 完全相同的条目 → 只保留一条
  • 后一条是前一条的子集 → 只保留前一条

Step 4: Summarize

将合并后的条目压缩为精炼形式:

原始

[round: 3] [DECISION] 支付超时改为 5s
  - Detail: 上游 SLA 从 3s 升级为 5s
[round: 5] [DECISION] 支付超时不能超过 8s
  - Detail: 超过会触发回退

压缩后

[DECISION] 支付超时设为 5s(上游 SLA 升级),上限 8s(防止回退)
  - 来源: round 3, 5
  - 关联: PaymentService.java

Step 5: Write Outputs

写入 increment(详细版)

  • 包含所有原始条目的完整记录
  • 用于追溯

写入 snapshot 更新(精炼版)

  • 只写入压缩后的摘要
  • 更新 snapshot 中受影响的章节

Step 6: Clear Buffer

清空 .ai-context/buffer.md

Step 7: Git Add

git add .ai-context/increments/
git add .ai-context/snapshot.md
git add .ai-context/buffer.md

Output

静默执行。完成后简要报告:

+ Compact complete:
  - 12 raw entries → 4 summarized entries
  - 2 groups merged, 1 conflict flagged
  - Increment: 2026-04-24_compact-session.md
  - Snapshot updated: Key Decisions, Constraints

Difference from /digest

/digest /compact
触发时机 soft 阈值 (5) compact 阈值 (8)
动作 直接写入 increment 先合并压缩,再写入
snapshot 更新 否(等 /evolve) 是(轻量更新)
目的 防止丢失 防止膨胀

典型流程

buffer 积累 → 达到 5 条 → /digest → increments
buffer 继续积累 → 达到 8 条 → /compact → snapshot 轻量更新 + increments
buffer 继续积累 → 达到 15 条 → 强制 /compact + /digest

Read the full file on GitHub · 117 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 117 lines · 20 tokens per session scan A 514c956a18e1

Subscribe to this mod's changes

lore-compact is a skill published in the GitHub repository koersliven/Lore (5 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 20 tokens to every session and 931 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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