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get_resume_brief

Retrieve a comprehensive cross-session resume brief when switching AI tools or starting new sessions. Includes user identity, project state, daily logs, recent context, top lessons, and suggested documents.

Instructions

跨会话/跨工具接续简报(v3.30 新增)。 / Cross-session, cross-tool resume brief.

**用途:v3.30 行业首家"一次调用拿到完整接续简报"的高层 API。**
用户切换工具(Claude Code → Codex/Cursor)或开新对话时,AI 调用本工具
一次即可拿到:用户身份 + 当前项目状态 + 今日日志 + 最近会话上下文 +
最近经验/决策 + 建议阅读的项目文档清单。结果用
``<engram-resume priority="high">`` XML 标签包裹,提示客户端 AI 优先遵守。

Purpose (v3.30): the "what does the next AI need to know in 30 seconds"
high-level endpoint. When users switch tools or open a new chat,
calling this once returns identity + project state + today's daily log
+ recent context + top lessons/decisions + suggested project docs to
read. Result is wrapped in ``<engram-resume priority="high">`` so client
AIs (Claude Code additionalContext, Codex system prompt, etc.) treat
it as high-priority reference context.

Lifecycle: **session start** — call before the first user message in a
new session when continuing prior work, or whenever the user says
things like "接着上次", "继续之前", "what were we doing".

Args:
    project_folder: 项目文件夹路径(可选)。留空只返回身份卡。 /
        Project folder (optional). Empty returns identity-only.
    token_budget: 输出 token 软上限(默认 2000,约 8000 字符)。 /
        Soft cap for output tokens (default 2000 ≈ 8000 chars).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_folderNo
token_budgetNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It describes the output format (wrapped in XML tags) and the effect of empty project_folder. However, it does not explicitly state that the tool is read-only or safe to call multiple times, nor does it disclose error conditions or permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with Chinese/English sections, Purpose, Lifecycle, and Args. Every sentence adds value, though it is slightly verbose. It is front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (combining multiple data sources) and the presence of an output schema, the description is fairly complete: it explains what the tool does, when to use it, and what parameters mean. It could mention read-only behavior, but overall it provides sufficient context for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description compensates by explaining both parameters: project_folder is optional and empty returns identity-only; token_budget is a soft cap with default 2000 ≈ 8000 chars. This adds meaningful context beyond the schema's simple defaults.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as a cross-session, cross-tool resume brief that returns identity, project state, daily log, recent context, lessons/decisions, and suggested docs. It distinguishes itself from sibling tools like get_identity_card, get_daily_log, etc., by consolidating their outputs into a single call.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit lifecycle guidance: call before the first user message in a new session when continuing prior work, or when the user says phrases like '接着上次'. It implies this is the consolidated alternative to individual getters, though it could explicitly state 'instead of calling each getter separately'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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