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.
npx skills add asherzj/ashers-agent-skills --skill context-gcgit clone --depth 1 https://github.com/asherzj/ashers-agent-skillsWrote 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.
[](https://agentmods.dev/skills/asherzj/ashers-agent-skills/context-gc)<a href="https://agentmods.dev/skills/asherzj/ashers-agent-skills/context-gc"><img src="https://agentmods.dev/badge/skills/asherzj/ashers-agent-skills/context-gc/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/asherzj/ashers-agent-skills/context-gc"><img src="https://agentmods.dev/badge/skills/asherzj/ashers-agent-skills/context-gc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.00978 |
| Opus 5 | $0.00028 | $0.00489 |
| Sonnet 5 | $0.00011 | $0.00196 |
| Haiku 4.5 | $0.00006 | $0.00098 |
Grade A, and why
context-gc 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 9d 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.
What it actually says
项目上下文垃圾回收
项目上下文应当可从领域语言、架构决策、接口契约、代码和测试重新构建。本 Skill 先做只读审计，再让用户选择修复项；没有用户明确选择时，不删除、不重写长期记录。
1. 确定权威来源
先读取仓库的 AGENTS.md 或 CLAUDE.md，以及其指向的领域文档和工单约定。通常按以下职责判断权威位置：
- 领域术语 →
CONTEXT.md； - 上下文关系和数据所有权 →
CONTEXT-MAP.md； - 难以回退且反直觉的取舍 → ADR；
- 接口形状 → 类型、Schema、IDL 或 OpenAPI；
- 行为约束 → 自动化测试；
- 当前实现 → 代码、配置和迁移；
- 当前工作 → 工单系统；
- 原始讨论 → 逐字稿、会议记录或消息线程，仅作证据。
仓库有自己的规则时以仓库规则为准。不要把实现细节搬进领域词汇表。
2. 只读审计
检查并给出具体证据：
- 重复的 ADR 编号、失效链接和无效的 superseded 指针；
- 同一事实存在多个权威副本；
- 文档与代码、Schema、测试或运行配置矛盾；
CONTEXT.md混入实现状态、任务进度或临时设计；- 架构文档仍描述已删除的模块、接口或依赖；
- 已完成、废弃或被取代的规格仍被当作当前规则；
- 临时兼容层、Feature Flag、旧 Adapter 或 TODO 没有删除条件和对应工单；
- 原始逐字稿中的未确认内容被升级为项目事实；
- 当前改动修改了代码语义，却没有同步相应的词汇、决策或行为证据。
把结果分成：
- 确认一致：无需动作；
- 可机械修复：编号、链接、索引等不涉及语义选择；
- 需要人类决策：存在多个可能的当前真相；
- 可归档或删除：已有明确替代物且无活跃引用。
报告每项的权威来源、冲突来源、建议动作和影响面。不要用文档的新旧时间戳代替语义判断。
3. 人类选择门禁
先展示审计结果，再让用户选择本轮修复项。删除、合并或改变长期语义必须逐项得到确认。发现真正的领域歧义时调用 grilling 和 domain-modeling；不能由 Agent 根据代码多数票决定业务含义。
4. 修复
按“一项事实、一个权威位置”处理：
- 修正权威来源；
- 其他位置改为引用或删除重复表述；
- 被替代的 ADR 使用明确的 superseded 指针，保留其历史理由；
- 原始逐字稿保留来源指针，不改写成规范；
- 临时结构补充删除条件、责任工单和重新评估触发条件；
- 只有术语或架构决策真实改变时才更新
CONTEXT.md或 ADR。
不要顺手重构业务代码。审计暴露出的代码工作应提出为独立工单，只在用户或仓库流程授权时发布，再按合适的交付流程推进。
5. 验证与完成
重新运行链接、引用、编号和仓库规定的文档检查；抽样用代码和测试交叉验证已修复内容。最终报告：
- 修复了哪些冲突；
- 哪些记录被标记为已取代；
- 哪些内容被删除或改为引用；
- 哪些问题转成了工单；
- 仍需人类决定的事项。
只有所有已选择修复项都完成且没有制造新的重复事实时，本轮垃圾回收才算完成。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 77 lines · 56 tokens per session scan A bffc2907b3a3
context-gc is a skill published in the GitHub repository asherzj/ashers-agent-skills (2 stars, last pushed 12d ago), licensed MIT. It adds 56 tokens to every session and 978 once invoked, about $0.0003 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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