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get_resume_brief

Read-onlyIdempotent

Call once at session start to get a complete resume brief: user identity, project state, today's log, recent context, top lessons, and docs to read. Use it when switching tools or continuing prior work.

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）。超出时结果带 omitted，正文末尾注明省略了什么。 /
        Soft cap for output tokens (default 2000 ≈ 8000 chars). When it cuts content,
        the result carries ``omitted`` and the brief ends with one line naming what was left out.
    include_resume_pack: Include structured ``project_resume_pack.v1`` in
        the JSON response. Defaults to false to preserve existing output.
    include_agent_context_pack: Include structured
        ``agent_context_pack.v1`` for delegated sub-agent briefing.
        Defaults to false to preserve existing output.
    agent_role: Role used to shape the optional agent context pack.
    task_summary: Current delegated task summary for agent-pack selection.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_resume_brief"
  }
}

Input Schema

Name	Required	Default
`agent_role`	No	orchestrator
`task_summary`	No
`token_budget`	No
`project_folder`	No
`include_resume_pack`	No
`include_agent_context_pack`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv4.13.0Jul 6, 2026

addedInput schema / properties / agent_role

Added value: +{
+  "default": "orchestrator",
+  "title": "Agent Role",
+  "type": "string"
+}

addedInput schema / properties / include_agent_context_pack

Added value: +{
+  "default": false,
+  "title": "Include Agent Context Pack",
+  "type": "boolean"
+}

addedInput schema / properties / include_resume_pack

Added value: +{
+  "default": false,
+  "title": "Include Resume Pack",
+  "type": "boolean"
+}

addedInput schema / properties / task_summary

Added value: +{
+  "default": "",
+  "title": "Task Summary",
+  "type": "string"
+}

Addedv3.30.1May 27, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already cover read-only/idempotent/non-destructive, and the description adds real context beyond them: the output is wrapped in <engram-resume priority="high"> for client AI prioritization, and truncation over token_budget is signaled via an `omitted` field plus a trailing explanatory line. The one gap is that it does not describe latency/cost of the aggregate call or what happens when no project_folder is supplied beyond 'identity-only'.

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

Conciseness3/5

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

Front-loaded with the key purpose and lifecycle, but the entire body is duplicated in Chinese and English, roughly doubling length without adding information; the 'v3.30 行业首家' marketing line is pure filler.

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?

For a six-parameter aggregate read tool with an output schema, the description supplies everything needed: trigger conditions, per-parameter semantics and defaults, output wrapping convention, and truncation signaling. Return value structure is covered by the output schema, so nothing critical is missing.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden — and it documents all six parameters, including defaults and effects: project_folder (empty = identity-only), token_budget (default 2000 ≈ 8000 chars, truncation behavior), include_resume_pack and include_agent_context_pack (default false to preserve existing output shape), agent_role, and task_summary (used to shape/select the agent pack).

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?

States a specific verb+resource (returns a complete resume brief in one call) and explicitly frames it as the high-level aggregate endpoint versus the finer-grained siblings in the list (get_identity_card, get_project_context, get_daily_log, get_recent_context, get_relevant_knowledge). The enumerated contents (identity + project state + daily log + recent context + lessons/decisions + suggested docs) make the scope unambiguous.

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?

Gives a concrete trigger — 'session start, before the first user message when continuing prior work' — plus example user phrases ('接着上次', '继续之前'). It does not explicitly say when to prefer it over sibling tools like get_user_context or get_recent_context, which it partly subsumes, so an agent must infer the routing.

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