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diff_resume_versions

Compare old and new resume data to generate a human-readable change summary at project level, highlighting additions, deletions, modifications, and reordering before PDF export.

Instructions

对比新旧 ResumeData,生成人类可读的变更摘要(项目粒度,类 git diff 风格)。

什么时候该调用

merge_into_resume 之后、render_pdf 之前,让用户确认改动。

覆盖

基本信息、项目经历(新增/删除/修改/重排)、工作/教育条目数、技能组变化。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
newYes
oldYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 discloses the output is a human-readable change summary at the project granularity, and lists covered areas. However, it doesn't clarify whether this is a read-only operation (it reads two data objects), what happens with invalid/mismatched data structures, or performance implications. Given no annotation coverage, this is acceptable but not rich.

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 compact and well-structured with clear headers ('什么时候该调用' and '覆盖'). Every line earns its place: the purpose, the usage timing, and the coverage scope. Could be slightly more concise by removing the literal backslash escapes in the code formatting, but it's efficient overall.

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?

The tool has 2 parameters with 0% schema description coverage, has nested objects, and an output schema exists. Given the complexity and that an output schema handles return values, the description adequately covers purpose, timing, and coverage scope. The only minor gap is not specifying the exact data shape expected for old/new beyond 'ResumeData' context, but since the output schema documents returns, overall completeness is solid.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. The description implies 'old' and 'new' are ResumeData objects by context (the tool diffs resume versions), even though the schema only types them as generic objects with additionalProperties:true. The description doesn't document parameter format or constraints beyond what's inferred, so it meets the baseline but doesn't excel given the 0% coverage gap.

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 verb ('diff'), the resource ('ResumeData versions'), and the specific output type ('human-readable change summary, project-level, like git diff'). It distinguishes itself from siblings by focusing on comparing old vs new resume versions, which is distinct from merge_into_resume and render_pdf in the sibling list.

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

Usage Guidelines5/5

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

Explicitly states WHEN to use it: 'after merge_into_resume, before render_pdf, to let the user confirm changes.' This direct call-stack positioning names the specific siblings it relates to and the temporal ordering. The coverage section further clarifies what it examines (basic info, projects, work/education counts, skill group changes).

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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