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.
git clone --depth 1 https://github.com/junyuan-fang/agentmemory-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/commands/junyuan-fang/agentmemory-skills/cross-context)<a href="https://agentmods.dev/commands/junyuan-fang/agentmemory-skills/cross-context"><img src="https://agentmods.dev/badge/commands/junyuan-fang/agentmemory-skills/cross-context/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/commands/junyuan-fang/agentmemory-skills/cross-context"><img src="https://agentmods.dev/badge/commands/junyuan-fang/agentmemory-skills/cross-context.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 | $0.00013 | $0.00182 |
| Opus 5.5 | $0.00005 | $0.00073 |
| Sonnet 5.5 | $0.00003 | $0.00036 |
| Haiku 4.5 | $0.00001 | $0.00018 |
Grade A, and why
cross-context 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 2mo 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
When the user references another platform ("继续昨天那个项目" / "上次我在 Telegram 说过…"), inject context from their other-platform user_keys.
Read the session's user_key from your agent / IM bridge's session data, then:
ccskill context $ARGUMENTS
Typical args:
--user-key <their key>(this person's stable id on the current platform)--person <name>(if mapped in data/identities.json)--days 30(longer lookback)--raw(skip LLM summary)
No mapping → prints nothing (expected). To map a person on a second platform,
edit data/identities.json (see data/identities.example.json).
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.
- 2mo ago First seen · 22 lines · 13 tokens per session scan A 1d6243654358
cross-context is a command published in the GitHub repository junyuan-fang/agentmemory-skills (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 13 tokens to every session and 182 once invoked, about $0.0001 per session on Opus 5.5. 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.
cross-context compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| cross-contextjunyuan-fang/agentmemory-skills | Command | 2 | 4mo ago | Apache-2.0 | A | 13 | Claude Code |
| minutes-ideassilverstein/minutes | Command | 1.6k | yesterday | MIT | A | 48 | Claude Code, OpenCode |
| learnReflexioAI/claude-smart | Command | 792 | today | Apache-2.0 | A | 14 | Claude Code |
| memory-storeverygoodplugins/mcp-automem | Command | 66 | yesterday | MIT | A | 10 | Claude Code |
| cc-memoryTheLobbi/claude | Command | 21 | 8d ago | MIT | A | 0 | Claude Code |
| analyze-contextRohiRIK/OpenLtm | Command | 29 | 9d ago | MIT | A | 39 | Claude Code |
| lians-recallLians-ai/Lians | Command | 17 | 5d ago | Apache-2.0 | A | 19 | Claude Code |