bmad-tea-evaluate

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Evaluate

评估

Overview

概述

Goal: Take an adopter from a described target through a scored development and held-out evaluation with named gaps and repairs, and finish it with the CI plan that enforces it.

Role: You are the Master Test Architect.

You will continue to operate with your given name, identity, and communication_style, merged with the details of this role description.

目标： 引导 adopter 从已描述的目标出发，完成带评分的 development 与 held-out 评估，识别并修复明确的缺口，最终交付用于落实这些要求的 CI 计划。

角色： 你是测试架构师负责人（Master Test Architect）。你将继续使用赋予你的姓名、身份和 communication_style，并将其与本角色描述中的详细信息合并。

Conventions

约定

Bare paths (e.g.
```
references/inspection.md
```
) resolve from the skill root.
```
{skill-root}
```
resolves to this skill's installed directory (where
```
customize.toml
```
lives).
```
{project-root}
```
is the nearest ancestor of the working directory that contains an
```
_bmad
```
directory.
```
{skill-name}
```
resolves to the skill directory's basename.
Resolve sibling files such as
```
references/...
```
and
```
assets/...
```
from
```
{skill-root}
```
.

裸路径（如
```
references/inspection.md
```
）相对于 skill 根目录解析。
```
{skill-root}
```
解析为此 skill 的安装目录（其中包含
```
customize.toml
```
）。
```
{project-root}
```
是工作目录中最近的、包含
```
_bmad
```
目录的祖先目录。
```
{skill-name}
```
解析为 skill 目录的 basename。
诸如
```
references/...
```
和
```
assets/...
```
等同级文件从
```
{skill-root}
```
解析。

On Activation

激活时

Before resolving customizations or running hooks, inspect

{project-root}/_bmad/custom/

for

bmad-testarch-evaluate.toml

and

bmad-testarch-evaluate.user.toml

. If either exists, stop and tell the user to run

npx --package=bmad-method-test-architecture-enterprise@3 tea-migrate-customizations --project-root {project-root}

. Resolve any reported manual merge, then start a fresh chat. Do not continue with default settings while legacy overrides remain.

在解析自定义配置或运行 hooks 之前，检查

{project-root}/_bmad/custom/

中是否存在

bmad-testarch-evaluate.toml

和

bmad-testarch-evaluate.user.toml

。如果其中任何一个存在，请停止并告知用户运行

npx --package=bmad-method-test-architecture-enterprise@3 tea-migrate-customizations --project-root {project-root}

。完成工具报告的任何手动合并后，让用户开始新的聊天。只要遗留覆盖配置仍然存在，就不得使用默认设置继续执行。

Step 1: Resolve the Workflow Block

步骤 1：解析 Workflow Block

Run:

uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --project-root {project-root} --key workflow

If the script fails, resolve the

workflow

block yourself by reading these three files in base → team → user order and applying the same structural merge rules as the resolver:

```
{skill-root}/customize.toml
```
— defaults

{project-root}/_bmad/custom/{skill-name}.toml

— team overrides

{project-root}/_bmad/custom/{skill-name}.user.toml

— personal overrides

Any missing file is skipped. Scalars override, tables deep-merge, arrays of tables keyed by

code

id

replace matching entries and append new entries, and all other arrays append.

运行：

uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --project-root {project-root} --key workflow

如果脚本失败，则按照 base → team → user 的顺序读取以下三个文件，并使用与 resolver 相同的结构合并规则，自行解析

workflow

block：

```
{skill-root}/customize.toml
```
— 默认值

{project-root}/_bmad/custom/{skill-name}.toml

— 团队覆盖配置

{project-root}/_bmad/custom/{skill-name}.user.toml

— 个人覆盖配置

缺失的文件将被跳过。标量值会被覆盖，表会深度合并，以

code

或

id

为键的表数组会替换匹配项并追加新项，所有其他数组则直接追加。

Step 2: Execute Prepend Steps

步骤 2：执行 Prepend Steps

Execute each entry in

{workflow.activation_steps_prepend}

in order before proceeding.

在继续之前，按顺序执行

{workflow.activation_steps_prepend}

中的每个条目。

Step 3: Load Persistent Facts

步骤 3：加载持久化事实

Treat every entry in

{workflow.persistent_facts}

as foundational context you carry for the rest of the workflow run. Entries prefixed

file:

are paths or globs resolved from

{project-root}

— expand them and load every matching file in lexical path order as facts. All other entries are facts verbatim.

将

{workflow.persistent_facts}

中的每个条目视为贯穿本次 workflow 运行的基础上下文。以

file:

为前缀的条目是相对于

{project-root}

解析的路径或 glob；展开它们，并按词法路径顺序加载每个匹配文件作为事实。其他所有条目均按原样作为事实。

Step 4: Load Config

步骤 4：加载配置

Run

uv run {project-root}/_bmad/scripts/resolve_config.py --project-root {project-root} --key core --key modules.tea

. If the script fails, merge

{project-root}/_bmad/config.toml

{project-root}/_bmad/custom/config.toml

and

{project-root}/_bmad/custom/config.user.toml

yourself, in that order, with the merge rules above. If

_bmad/config.toml

is missing or has no

modules.tea

table, tell the user TEA is not set up, ask them to run

bmad setup tea

first, and stop.

Each

core

and

modules.tea

key is available as

{<key>}

, and as

config.<key>

in later steps. Replace

{project-root}

inside a value with the project root. Setup answers are strings: read

"true"

and

"false"

as booleans.

{tea_evaluations_folder}

{workflow.evaluations_folder}

, relative to

{project-root}

运行：

uv run {project-root}/_bmad/scripts/resolve_config.py --project-root {project-root} --key core --key modules.tea

。如果脚本失败，则按照上述合并规则，依次自行合并

{project-root}/_bmad/config.toml

、

{project-root}/_bmad/custom/config.toml

和

{project-root}/_bmad/custom/config.user.toml

。如果

_bmad/config.toml

缺失或没有

modules.tea

表，则告知用户尚未设置 TEA，请其先运行

bmad setup tea

，然后停止。

每个

core

和

modules.tea

键在后续步骤中均可作为

{<key>}

和

config.<key>

使用。将值中的

{project-root}

替换为项目根目录。设置项答案均为字符串：将

"true"

和

"false"

读取为布尔值。

{tea_evaluations_folder}

即

{workflow.evaluations_folder}

，其路径相对于

{project-root}

。

Step 5: Greet the User

步骤 5：问候用户

Greet

{user_name}

, speaking in

{communication_language}

使用

{communication_language}

与

{user_name}

打招呼。

Step 6: Execute Append Steps

步骤 6：执行 Append Steps

Execute each entry in

{workflow.activation_steps_append}

in order.

Activation is complete. Begin the workflow below.

按顺序执行

{workflow.activation_steps_append}

中的每个条目。

激活完成。开始执行下面的 workflow。

Workflow

Evaluate is one continuous loop over twelve stages, run inline rather than as separate step files: each stage's craft lives in its own

references/

guide, loaded when that stage is reached. Work under

{tea_evaluations_folder}

unless the adopter names another location. On resume, read the existing inspection record,

evaluation.json

, any

requirements.md

, any

authoring-log.md

, any

<evaluation-folder>/ci/evaluation-ci-plan.json

, and any

{test_artifacts}/evaluate/<evaluationId>/gap-report.md

before choosing a stage. Before Stage 3, require the adopter's confirmation in the statement and compare

requirements.digest

with eval-quality's

digestBytes

over the committed file; otherwise return to intake. Continue from the first incomplete stage, or the adopter's requested stage when its prerequisites hold.

assets/README.md

says how to fill each template under

assets/

Read

references/authoring-routing.md

before delegating any authoring work. Use its bounded worker tasks and authoring ledger throughout the loop when the host supports subagents.

Never improvise the stage's craft yourself, and never compute a verdict, score, or pass/fail decision outside

eval-quality

's own CLI (AD-6): a verdict this skill computed itself would not be one

eval-quality

sealed.

Evaluate 由十二个阶段组成一个连续循环，应内联执行，而不是拆分为独立的 step 文件：每个阶段的具体实践都记录在其对应的

references/

指南中，进入该阶段时再加载。除非 adopter 指定了其他位置，否则应在

{tea_evaluations_folder}

下工作。恢复执行时，在选择阶段之前，读取现有的 inspection 记录、

evaluation.json

、任何

requirements.md

、任何

authoring-log.md

、任何

<evaluation-folder>/ci/evaluation-ci-plan.json

，以及任何

{test_artifacts}/evaluate/<evaluationId>/gap-report.md

。在进入阶段 3 之前，要求 adopter 在声明中作出确认，并将

requirements.digest

与 eval-quality 针对已提交文件计算的

digestBytes

进行比较；否则返回 intake。前提条件满足时，从第一个未完成的阶段继续，或从 adopter 指定的阶段继续。

assets/README.md

说明了如何填写

assets/

下的每个模板。

在委派任何 authoring 工作之前，读取

references/authoring-routing.md

。如果宿主支持 subagents，应在整个循环中使用其中有界的 worker 任务和 authoring ledger。

绝不要自行即兴实施某阶段的具体实践，也绝不要在 eval-quality 自身的 CLI（AD-6）之外计算 verdict、score 或 pass/fail 判定：由该 skill 计算出的 verdict 不会成为 eval-quality 封存的 verdict。

Stage 1: Inspection

阶段 1：Inspection

Inspect the target and identify its kind. Load

references/inspection.md

检查目标并确定其类型。加载

references/inspection.md

。

Stage 2: Intake

阶段 2：Intake

Capture behavioral requirements and constraints the adopter confirms. Load

references/intake.md

捕获由 adopter 确认的行为需求和约束。加载

references/intake.md

。

Stage 3: Corpus

阶段 3：Corpus

Design the probe corpus. Load

references/corpus.md

设计 probe corpus。加载

references/corpus.md

。

Stage 4: Contract

阶段 4：Contract

Author the Behavioral Evaluation Contract. Load

references/contract.md

. Stamp its

sourceSpecDigest

with eval-quality's

digestBytes

over the confirmed

requirements.md

bytes, matching

evaluation.json

requirements.digest

编写 Behavioral Evaluation Contract。加载

references/contract.md

。使用 eval-quality 的

digestBytes

对已确认的

requirements.md

字节计算结果，将其写入

sourceSpecDigest

，并确保与

evaluation.json

中的

requirements.digest

匹配。

Stage 5: Oracles

阶段 5：Oracles

Design oracles and rubrics. Load

references/oracles.md

设计 oracles 和 rubrics。加载

references/oracles.md

。

Stage 6: Adapters

阶段 6：Adapters

Scaffold the execution-target registry and adapters. Load

references/adapters.md

When the contract, oracles and registry are filled, copy

assets/evaluator-conditions.template.json

policy/evaluator-conditions.json

and fill the target's

modelSnapshot

and

systemPromptDigest

. A

tea-skill-runner

registry needs a real model snapshot. For a deterministic evaluator with a rubric, declare

evaluation.json.judge

and fill

judge.modelSnapshot

; remove the unused template

judge

block for other cases. Ensure

policy/scoring-policy.json

has been copied from the installed template and filled if any probe takes the

controlled-mutation

historical

, or

gameability

route. Ask the adopter for its

policyId

and thresholds, then set

evaluation.json.trials

at or above

minimumTrialCount

Before the first

tea-evaluate check

, load

references/mutation.md

and author every

mutations/<mutationId>.mutation.json

named by a Stage 3

controlled-mutation

probe. Use an adopter-owned target, a single exact replacement, and the probe's observable defect signature. Refresh

corpus-index.json

after writing those files. For an adopter installation, run

npm exec --prefix {tea_evaluations_folder} -- tea-evaluate digest --evaluation <evaluation-folder>

; for TeA's own package, run

node cli/evaluate.js digest --evaluation <evaluation-folder>

from the repository root. Stage 6 preflight qualifies the nominated probes; Stage 8 inspects their manifestation and rollback evidence and expands the mutation set.

For an adopter installation, run

npm exec --prefix {tea_evaluations_folder} -- tea-evaluate check --evaluation <evaluation-folder>

, then

npm exec --prefix {tea_evaluations_folder} -- eval-quality compile --in <evaluation-folder>/contract.json --out <evaluation-folder>/compiled-contract.json

, then

npm exec --prefix {tea_evaluations_folder} -- eval-quality seal --in <evaluation-folder>/contract.json --out <evaluation-folder>/sealed-brief.json

. For TeA's own package, run

node cli/evaluate.js check --evaluation <evaluation-folder>

, then

./node_modules/.bin/eval-quality compile --in <evaluation-folder>/contract.json --out <evaluation-folder>/compiled-contract.json

, then

./node_modules/.bin/eval-quality seal --in <evaluation-folder>/contract.json --out <evaluation-folder>/sealed-brief.json

from the repository root. The local CLI and binary use that root's one eval-quality installation. Stop at the first nonzero exit. Report its command, exit code and stderr before changing the artifact and rerunning that stage.

After seal succeeds, copy

assets/evaluation-folder.gitignore

<evaluation-folder>/.gitignore

before the first preflight creates

runs/

. Before a live preflight, follow the Git isolation procedure in

references/run.md

; Git worktrees share refs even when their working files are separate. For an adopter installation, run

npm exec --prefix {tea_evaluations_folder} -- tea-evaluate preflight --evaluation <evaluation-folder> --partition development

; for TeA's own package, run

node cli/evaluate.js preflight --evaluation <evaluation-folder> --partition development

from the repository root. This verifies the selected registry can launch and satisfy its clean control. The flag is required only when

evaluation.json

declares a

partitionPlan

, and a preflight with no

--partition

over one exits 64. Held-out preflight (

--partition held-out

) runs only after the development review. Stop and report the command, exit code and stderr on failure; complete adapter wiring only after preflight succeeds.

搭建 execution-target registry 和 adapters 的脚手架。加载

references/adapters.md

。

当 contract、oracles 和 registry 均已填写完成后，将

assets/evaluator-conditions.template.json

复制为

policy/evaluator-conditions.json

，并填写目标的

modelSnapshot

和

systemPromptDigest

。tea-skill-runner registry 需要真实的 model snapshot。对于带 rubric 的确定性 evaluator，声明

evaluation.json.judge

并填写

judge.modelSnapshot

；其他情况则删除未使用的模板

judge

block。确保已从安装模板复制

policy/scoring-policy.json

；如果任何 probe 采用

controlled-mutation

、

historical

或

gameability

路线，则填写该文件。向 adopter 询问其

policyId

和 thresholds，然后将

evaluation.json.trials

设置为大于或等于

minimumTrialCount

的值。

在首次运行

tea-evaluate check

之前，加载

references/mutation.md

，并为阶段 3 中每个

controlled-mutation

probe 所命名的

mutations/<mutationId>.mutation.json

编写内容。使用由 adopter 拥有的目标、一次精确替换，以及该 probe 的可观察缺陷签名。写入这些文件后，刷新

corpus-index.json

。对于 adopter 的安装实例，运行

npm exec --prefix {tea_evaluations_folder} -- tea-evaluate digest --evaluation <evaluation-folder>

；对于 TeA 自身的 package，在 repository 根目录下运行

node cli/evaluate.js digest --evaluation <evaluation-folder>

。阶段 6 的 preflight 负责验证候选 probes 是否合格；阶段 8 将检查其表现和回滚证据，并扩展 mutation 集合。

对于 adopter 的安装实例，运行

npm exec --prefix {tea_evaluations_folder} -- tea-evaluate check --evaluation <evaluation-folder>

，然后运行

npm exec --prefix {tea_evaluations_folder} -- eval-quality compile --in <evaluation-folder>/contract.json --out <evaluation-folder>/compiled-contract.json

，最后运行

npm exec --prefix {tea_evaluations_folder} -- eval-quality seal --in <evaluation-folder>/contract.json --out <evaluation-folder>/sealed-brief.json

。对于 TeA 自身的 package，在 repository 根目录下运行

node cli/evaluate.js check --evaluation <evaluation-folder>

，然后运行

./node_modules/.bin/eval-quality compile --in <evaluation-folder>/contract.json --out <evaluation-folder>/compiled-contract.json

，最后运行

./node_modules/.bin/eval-quality seal --in <evaluation-folder>/contract.json --out <evaluation-folder>/sealed-brief.json

。本地 CLI 和 binary 使用该根目录下唯一的 eval-quality 安装。在首次出现非零退出码时停止；报告相应命令、退出码和 stderr，然后才能修改 artifact 并重新运行该阶段。

seal 成功后，在首次 preflight 创建

runs/

之前，将

assets/evaluation-folder.gitignore

复制到

<evaluation-folder>/.gitignore

。在 live preflight 之前，遵循

references/run.md

中的 Git 隔离流程；即使工作文件彼此分离，Git worktrees 仍会共享 refs。对于 adopter 的安装实例，运行

npm exec --prefix {tea_evaluations_folder} -- tea-evaluate preflight --evaluation <evaluation-folder> --partition development

；对于 TeA 自身的 package，在 repository 根目录下运行

node cli/evaluate.js preflight --evaluation <evaluation-folder> --partition development

。此步骤验证选定的 registry 能够启动并满足 clean control。仅当

evaluation.json

声明了

partitionPlan

时才必须提供该 flag；如果针对多个 partition 的 preflight 未提供

--partition

，则会以 64 退出。held-out preflight（

--partition held-out

）只能在 development review 完成后运行。失败时停止并报告命令、退出码和 stderr；仅在 preflight 成功后完成 adapter wiring。

Stage 7: Evaluator

阶段 7：Evaluator

Choose or build the evaluation layer. Load

references/evaluator.md

选择或构建 evaluation layer。加载

references/evaluator.md

。

Stage 8: Mutation

阶段 8：Mutation

Apply and roll back controlled mutations. Load

references/mutation.md

应用并回滚 controlled mutations。加载

references/mutation.md

。

Stage 9: Harness

阶段 9：Harness

Scaffold the runner and scoring policy. Load

references/harness.md

搭建 runner 和 scoring policy 的脚手架。加载

references/harness.md

。

Stage 10: Run

阶段 10：Run

Run the clean and mutated arms and score them. Load

references/run.md

运行 clean arm 和 mutated arm 并进行评分。加载

references/run.md

。

Stage 11: Gaps

阶段 11：Gaps

Interpret a weak result and close the gap. Load

references/gaps.md

解读薄弱结果并弥合缺口。加载

references/gaps.md

。

Stage 12: CI

阶段 12：CI

Inspect the adopter's repository, place each check in a tier, write

<evaluation-folder>/ci/evaluation-ci-plan.json

and hand it to

bmad-tea-framework

with CI setup scope. Load

references/ci.md

检查 adopter 的 repository，将每项 check 归入相应 tier，编写

<evaluation-folder>/ci/evaluation-ci-plan.json

，并以 CI setup scope 将其移交给

bmad-tea-framework

。加载

references/ci.md

。

On Complete

完成时

Run:

uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --project-root {project-root} --key workflow.on_complete

If the resolver succeeds and returns a non-empty

workflow.on_complete

, execute that value as the final terminal instruction before exiting.

If the resolver fails, returns no output, or resolves an empty value, skip the hook and exit normally.

运行：

uv run {project-root}/_bmad/scripts/resolve_customization.py --skill {skill-root} --project-root {project-root} --key workflow.on_complete

如果 resolver 成功并返回非空的

workflow.on_complete

，则在退出前将该值作为最终终止指令执行。

如果 resolver 失败、未返回任何输出或解析出的值为空，则跳过该 hook 并正常退出。