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get_resume_brief

Retrieves a complete resume brief including user identity, project state, recent logs, context, lessons, and suggested documents when switching tools or starting a new session.

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 the full burden. It describes the output format (XML wrapper) and lifecycle, but lacks details on error handling, rate limits, or side effects. It does not specify what happens if token_budget is exceeded or if project_folder is invalid. Adequate but not fully transparent.

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

Conciseness5/5

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

The description is well-structured with separate sections for purpose, lifecycle, and args. It prioritizes key information upfront and uses concise headings. Every sentence adds value, and bilingual completeness is maintained without redundancy. It is appropriately sized for a complex composite tool.

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

Completeness5/5

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

Given the tool's complexity and presence of output schema, the description is nearly complete. It covers what is returned, when to call, parameter behavior, and output format. The existence of sibling tools for individual pieces does not reduce the need for this aggregate tool's description, which is thorough.

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 description coverage is 0%, but the description compensates well by explaining both parameters: project_folder (optional, empty returns identity-only) and token_budget (soft cap, default 2000). This adds significant meaning beyond the schema's minimal defaults and types, though it could be more precise about output behavior with different inputs.

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: a high-level endpoint returning a composite resume brief including identity, project state, logs, context, lessons, decisions, and suggested docs. It distinguishes from sibling tools (e.g., get_identity_card, get_project_context) by aggregating multiple pieces into one call, making the unique value evident.

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 usage guidance: call at session start when continuing prior work or when user says phrases like '接着上次'. It explains the lifecycle and expected client AI behavior. However, it does not explicitly state when not to use this tool or mention alternative tools for specific sub-tasks, leaving some ambiguity.

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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