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chain_score_report

Generates a 5-dimension scoring report from chain run results, evaluating functional path pass rate, API success rate, state diff consistency, schema validation, and observability error collection, outputting weighted total score and grade.

Instructions

对 chain_spec_run 结果输出 5 维评分报告:功能链路(步骤通过率)、技术链路(API/网络成功率)、一致性(状态 diff 通过率)、契约(API schema 校验)、可观测性(错误采集质量)。输出加权总分和等级。先做进现有 MCP,后续再剥离。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
runIdNo可选,链路运行 ID
resultNochainResult 的别名
chainResultNochain_spec_run 的完整返回结果对象
Behavior2/5

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

With no annotations, the description carries full behavioral disclosure burden. It only describes output content and does not mention side effects, read-only nature, required permissions, or any safety traits. For a reporting tool, it is likely read-only, but this is not stated, leaving behavioral assumptions to the agent.

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 concise and front-loaded with the main purpose and dimensions. It avoids redundancy but includes a note about future separation. One sentence could be considered extraneous, but overall it efficiently conveys the tool's function.

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 description explains the output structure (5 dimensions, weighted total score, grade) without an output schema. It is sufficient for an agent to understand what the tool returns. However, it lacks specifics on scoring methodology or scale, which could be needed for precise invocation.

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 100% with brief descriptions for each parameter (runId, result as alias, chainResult). The tool description adds context that the result comes from chain_spec_run, but does not add significant meaning beyond the schema. Baseline 3 is appropriate.

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 generates a 5-dimensional scoring report for chain_spec_run results, listing each dimension: functionality, technology, consistency, contract, and observability. This specific verb+resource combination distinguishes it from sibling tools like chain_spec_run (which runs the chain) and other reporting tools.

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

Usage Guidelines3/5

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

The description implies usage after obtaining chain_spec_run results, but does not explicitly state when to use this tool versus alternatives. It lacks when-not guidance or alternative suggestions. The phrase '先做进现有 MCP,后续再剥离' provides context but not actionable usage instructions.

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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