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 modelstudioai/cli --skill bailian-memorygit clone --depth 1 https://github.com/modelstudioai/cliWrote 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/modelstudioai/cli/bailian-memory)<a href="https://agentmods.dev/skills/modelstudioai/cli/bailian-memory"><img src="https://agentmods.dev/badge/skills/modelstudioai/cli/bailian-memory/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/modelstudioai/cli/bailian-memory"><img src="https://agentmods.dev/badge/skills/modelstudioai/cli/bailian-memory.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 | $0.00209 | $0.02827 |
| Opus 5.5 | $0.00084 | $0.01131 |
| Sonnet 5.5 | $0.00042 | $0.00565 |
| Haiku 4.5 | $0.00021 | $0.00283 |
Grade A, and why
bailian-memory 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 yesterday.
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.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
个人长期记忆
让用户在自己的 Agent 中自然地积累和使用生活、工作记忆。采用纯 Skill：仅在宿主加载并执行时工作，不承诺每轮调用、会话结束回调或后台执行。
读取本 Skill、检查本地启用状态与发送云端请求是三个不同步骤。 前两步不以已经启用为前提；只有云端个人记忆读写需要启用授权。安装 Skill 不代表用户已授权上传。
执行任何 bl 命令前，先读取共享协议 bailian-protocol，遵循鉴权、版本预检、调用归因和高风险确认。协议缺失不妨碍识别记忆意图或解释启用流程；但执行命令前须补齐，提示 bl skill init，不能静默退回内置记忆并声称本服务已工作。
Call attribution: Examples below and in reference/ stay bare bl …. When running a command, wrap it with bailian-protocol → Call attribution (bash or PowerShell). One sample for this skill (BAILIAN_SKILL_NAME=bailian-memory; replace codex with this host). Fill <bound-user-id> / <bound-workspace-id> from ~/.bailian/personal-memory/config.json; do not invent ids. Command names in the tables below are arguments only.
BAILIAN_CALLER_TYPE=agent BAILIAN_CALLER_NAME=codex BAILIAN_SKILL_NAME=bailian-memory BAILIAN_SKILL_VERSION=2.5.0 bl memory list --user-id <bound-user-id> --workspace-id <bound-workspace-id> --page-size 1 --output json
入口与范围
- 个人记忆：遇到上述触发意图，先读取用户级
~/.bailian/personal-memory/config.json；不能在读取前以“用户尚未启用”为由跳过本 Skill。同一会话状态已知可复用，启用/暂停后刷新。状态定义与旧配置迁移见 初始化。 - 配置不存在：读取 初始化，自然回答当前问题，同时简短提出一次云端记忆启用引导。不先索要凭证，不上传，不宣称已保存。用户拒绝或未回应时继续对话，本会话不反复推销；再次明确要求启用时再继续。
- 配置
status=paused：不自动恢复或重新发起启用提示。明确恢复请求才进入恢复流程。配置status=initializing时按初始化文档续接已有身份和资源，不当作暂停或首次新用户；配置损坏时停止自动操作并说明。 - 只有
status=active、有效身份与已记录的启用授权齐全时，才能自动读写；已有授权不重复确认。未触发个人记忆的普通问答直接完成，不引导配置。 - 明确的百炼应用记忆管理：按用户指定资源操作，直接使用 命令参考，不创建个人身份或 Profile，不将应用数据写入个人记忆。
- 用户说“这次别记”“暂停”“别用以前的记忆”时，先处理控制意图，再考虑自动读写。
个人模式固定使用配置中的 Workspace 和 user_id；省略 library/project 参数，使用服务端默认库及默认 observation 规则。不能用临时随机 user_id、当前目录或猜测的账号名替换身份。应用资源管理与个人模式严格区分范围。
与宿主内置记忆的分工
用户已启用本服务时，这些个人记忆操作优先使用 bl memory，不因为存在 memory_search、memory 或 USER.md 就绕开本 Skill。不要默认双写内置记忆，不批量迁移宿主已有资料。宿主内置记忆的容量限制不适用于本服务。
用户明确选择内置记忆或更高优先级宿主规则限定工具时遵从该选择/规则；必要时说明实际使用了哪套记忆，不能将内置工具成功报告成百炼保存成功。本服务不可用时也不静默换用另一套存储。
What ships with it
6 files 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.
- yesterday Changed · +6 lines e912c021a1ab
- 2d ago Changed cf8f8708eaee
- 4d ago First seen · 104 lines · 209 tokens per session scan A ad1cbb2c4447
bailian-memory is a skill published in the GitHub repository modelstudioai/cli (363 stars, last pushed yesterday), licensed Apache-2.0. It adds 209 tokens to every session and 2,827 once invoked, about $0.0008 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 2026-10-21.
Other skills, from other repositories
context-boundary-reporter
Write a machine-checkable context boundary receipt from provided project context files.
doris-debug-resource-isolation
Use for Doris Workload Group / resource tag queue starvation, CPU/memory isolation leaks, and workload policy debugging. Commands: SHOW WORKLOAD GROUPS, EXPLAIN resource.
cf-learn
Extract educational notes for the human from the conversation (unlike /cf-remember, which stores project memory for AI recall). TRIGGER — substantial new technical knowledge, a debugging breakthrough, an architecture decision explained, or a complex explanation worth keeping; the user says "explain what we learned"…
cf-remember
Save project knowledge to docs/memory for AI recall (unlike /cf-learn, which writes educational notes for the human). TRIGGER — "remember this", "save this to memory", "document what we did", "capture this decision", "write this down", "note this", "record this convention"; after a non-obvious bug fix → bugs/, an…
cf-scan
Scan the project and populate memory (architecture, conventions, stack, features). Triggers: "scan the project", "scan the codebase", "bootstrap memory", "populate memory", "analyze the project". Token-heavy — always warn before proceeding.
cf-ask
Quick Q&A about the codebase → docs/memory. Use for focused project questions — e.g. "how does X work?", "where is Y defined?", "what's the flow for Z?", "explain this module", "why is this done this way?". Unlike /cf-research, one answer.