ai-sdlc-delivery-handoff-review

Compare original and translation side by side

🇺🇸

Original

English
🇨🇳

Translation

Chinese

ai-sdlc-delivery-handoff-review: Delivery Handoff Review

ai-sdlc-delivery-handoff-review:交付交接评审

Internal AI SDLC skill, not client-facing by default. Every rule below is important to follow. None of it can be skipped. Before producing the final artifact, confirm required inputs, target audience, missing facts, output format, and constraints when they are unclear. Do not invent missing information. Ask concise clarification questions when required inputs are absent.
内部AI SDLC技能,默认不面向客户。 以下每条规则都必须遵守,不可跳过任何一条。 在生成最终成果前,若对所需输入、目标受众、缺失信息、输出格式及约束条件存在疑问,需先进行确认。 不得编造缺失信息。当所需输入缺失时,需提出简洁的澄清问题。

0. Skill Card

0. 技能卡片

  • Skill name:
    ai-sdlc-delivery-handoff-review
  • Primary audience: Delivery
  • Supporting audience: PM, BA, QA, Dev Lead
  • Audience tags: PM, BA, QA, Dev
  • SDLC stage: Engineering handoff quality gate
  • Purpose: Run the final quality gate on the delivery package before it is treated as ready for implementation planning or handoff.
  • Output: Handoff readiness score, remaining blockers, contradictions, and execution risks
  • 技能名称:
    ai-sdlc-delivery-handoff-review
  • 核心受众:交付团队
  • 支持受众:PM(产品经理)、BA(业务分析师)、QA(质量保证)、Dev Lead(开发负责人)
  • 受众标签:PM、BA、QA、Dev
  • SDLC阶段:工程交接质量 gate
  • 目的:在交付包被认定为可进入实施规划或交接阶段前,运行最终质量 gate 进行检查。
  • 输出:交接就绪度评分、剩余阻塞点、矛盾点及执行风险

0.1 Required Inputs

0.1 必需输入

  • Delivery spec, stories, acceptance criteria, and supporting context.
  • Known constraints, dependencies, and ownership expectations.
  • Target implementation or planning audience.
  • 交付规格说明、需求故事、验收标准及相关上下文。
  • 已知约束条件、依赖关系及职责预期。
  • 目标实施或规划受众。

0.2 Clarification Rules

0.2 澄清规则

  • Ask concise questions before finalizing when role, artifact, requirements, scope, audience, or constraints are unclear.
  • If optional information is missing, mark it as
    TBD
    ,
    Not provided
    , or
    Assumption
    instead of inventing it.
  • Separate confirmed facts from assumptions and open questions.
  • Do not proceed to downstream synthesis when a required upstream artifact or decision is missing.
  • 当角色、成果物、需求、范围、受众或约束条件不明确时,需先提出简洁的问题再完成工作。
  • 若可选信息缺失,标记为
    TBD
    (待确定)、
    Not provided
    (未提供)或
    Assumption
    (假设),不得编造。
  • 将已确认事实与假设、未解决问题分开。
  • 当必需的上游成果物或决策缺失时,不得进行下游整合工作。

0.2.1 Flow Mode Flags

0.2.1 流程模式标识

  • Support two explicit execution flags:
    --quick-flow
    and
    --full-flow
    .
  • If both flags are supplied,
    --full-flow
    takes precedence because it is the stricter mode.
  • --quick-flow
    : move fast, make high-quality progress with available context, avoid clarification questions unless continuing would create material product, security, compliance, data-loss, or irreversible implementation risk.
  • In
    --quick-flow
    , use documented assumptions, recommended defaults, existing repository patterns, and the nearest available artifact evidence; record important assumptions and decisions in
    decision-log.md
    .
  • In
    --quick-flow
    , run only focused checks that are directly relevant, cheap, and likely to catch regressions for the requested work; report any skipped broader checks as residual risk.
  • --full-flow
    : ask concise clarification questions when inputs, scope, ownership, acceptance criteria, or decisions are unclear; do not silently assume material requirements.
  • In
    --full-flow
    , verify upstream and downstream artifacts, decision-log entries, traceability links, acceptance criteria, and validation evidence before finalizing.
  • In
    --full-flow
    , run or recommend the skill-appropriate gates, reviews, scripts, and validation commands needed for end-to-end confidence; document any blocked verification explicitly.
  • When neither flag is supplied, follow the skill default rules and choose the least risky behavior for the request size and domain.
  • 支持两种明确的执行标识:
    --quick-flow
    --full-flow
  • 若同时提供两种标识,
    --full-flow
    优先,因为它是更严格的模式。
  • --quick-flow
    :快速推进,利用现有上下文开展高质量工作,除非继续推进会产生重大产品、安全、合规、数据丢失或不可逆实施风险,否则避免提出澄清问题。
  • --quick-flow
    模式下,使用已记录的假设、推荐默认值、现有仓库模式及最接近的可用成果物证据;将重要假设和决策记录在
    decision-log.md
    中。
  • --quick-flow
    模式下,仅运行与请求工作直接相关、成本低且可能发现回归问题的针对性检查;将任何跳过的更广泛检查报告为残留风险。
  • --full-flow
    :当输入、范围、职责、验收标准或决策不明确时,提出简洁的澄清问题;不得默认重要需求。
  • --full-flow
    模式下,在完成工作前验证上下游成果物、决策日志条目、可追溯链接、验收标准及验证证据。
  • --full-flow
    模式下,运行或推荐适合技能的gate、评审、脚本及验证命令,以确保端到端可信度;明确记录任何受阻的验证工作。
  • 当未提供任何标识时,遵循技能默认规则,并根据请求规模和领域选择风险最低的行为。

0.3 Output Rules

0.3 输出规则

  • Keep output structured with headings and bullets.
  • Make findings, gaps, risks, and blockers explicit.
  • Tie recommendations to evidence from the provided artifact,
    specs-refiniment/<feature-name>/<file.md>
    workspace, or user context.
  • Include role ownership when the output creates follow-up work for BA, QA, Dev, PM, or Delivery.
  • Return progress, completion, validation, and handoff summaries directly in the Codex response.
  • Before the final response, emit the
    ai-sdlc-handoff/v1
    contract with
    result
    ,
    blockers
    ,
    next_required
    , and
    next_optional
    ; every action includes
    reason
    ,
    command
    , and
    expected_artifact
    .
  • Do not create
    summary.txt
    ,
    *-summary.txt
    , or another standalone summary file unless the user explicitly requests one.
  • Keep durable writes limited to the canonical lifecycle artifacts, decision log, human-readable index, and
    _ai_sdlc
    machine files.
  • Let shared helpers migrate legacy paths on the next write; never overwrite or manually merge divergent legacy and canonical files.
  • 输出需结构化,使用标题和项目符号。
  • 明确列出发现的问题、缺口、风险及阻塞点。
  • 建议需与提供的成果物、
    specs-refiniment/<feature-name>/<file.md>
    工作区或用户上下文的证据关联。
  • 当输出为BA、QA、Dev、PM或交付团队产生后续工作时,需明确角色职责。
  • 直接在Codex响应中返回进度、完成情况、验证及交接摘要。
  • 在最终响应前,输出包含
    result
    blockers
    next_required
    next_optional
    ai-sdlc-handoff/v1
    契约;每个操作需包含
    reason
    command
    expected_artifact
  • 除非用户明确要求,否则不得创建
    summary.txt
    *-summary.txt
    或其他独立摘要文件。
  • 仅将持久化写入限制在标准生命周期成果物、决策日志、人类可读索引及
    _ai_sdlc
    机器文件中。
  • 让共享助手在下次写入时迁移旧路径;不得覆盖或手动合并不一致的旧文件与标准文件。

0.4 Artifact Routing

0.4 成果物路由

  • Maintain a feature decision log whenever this skill records, resolves, changes, or depends on a product, delivery, QA, security, validation, branching, implementation, or rollout decision.
  • For PM, BA, QA, Delivery, discovery, planning, refinement, and readiness work, write decisions to
    specs-refiniment/<feature-name>/decision-log.md
    .
  • For developer implementation SDD work, write decisions to
    specs/<feature-name>/decision-log.md
    .
  • Each decision-log entry must include date, decision, context or evidence, options considered when relevant, owner, status, and links to affected artifacts, tasks, tests, or validation evidence.
  • Use this exact decision-log structure:
    markdown
    # Decision Log
    
    | ID | Date | Status | Owner | Decision | Context/Evidence | Options Considered | Affected Artifacts | Validation/Trace Links |
    | --- | --- | --- | --- | --- | --- | --- | --- | --- |
    | DEC-001 | YYYY-MM-DD | proposed / accepted / superseded / rejected | role or name | concise decision | source facts, artifact links, or evidence | option A; option B; recommended default | affected docs, tasks, code, tests, or rollout notes | requirement IDs, test IDs, validation commands, PRs, commits, or tickets |
  • When writing or updating files, place PM, BA, QA, Delivery, discovery, planning, refinement, and readiness artifacts at
    specs-refiniment/<feature-name>/<file.md>
    .
  • Use the path pattern
    specs-refiniment/<feature-name>/<file.md>
    ; choose a stable feature slug when known, otherwise use
    tbd-<short-topic>
    for
    <feature-name>
    .
  • Do not write this skill's output into
    specs/
    ; that folder is reserved for developer implementation SDD artifacts.
  • If the user explicitly asks to convert a refined artifact into developer implementation work, hand off to
    $ai-sdlc-sdd
    .
  • 每当该技能记录、解决、更改或依赖产品、交付、QA、安全、验证、分支、实施或发布决策时,需维护功能决策日志。
  • 对于PM、BA、QA、交付团队的探索、规划、细化及就绪工作,将决策写入
    specs-refiniment/<feature-name>/decision-log.md
  • 对于开发人员的实施SDD工作,将决策写入
    specs/<feature-name>/decision-log.md
  • 每个决策日志条目必须包含日期、决策内容、上下文或证据、相关备选方案(如有)、负责人、状态及关联成果物、任务、测试或验证证据的链接。
  • 使用以下精确的决策日志结构:
    markdown
    # Decision Log
    
    | ID | Date | Status | Owner | Decision | Context/Evidence | Options Considered | Affected Artifacts | Validation/Trace Links |
    | --- | --- | --- | --- | --- | --- | --- | --- | --- |
    | DEC-001 | YYYY-MM-DD | proposed / accepted / superseded / rejected | role or name | concise decision | source facts, artifact links, or evidence | option A; option B; recommended default | affected docs, tasks, code, tests, or rollout notes | requirement IDs, test IDs, validation commands, PRs, commits, or tickets |
  • 当写入或更新文件时,将PM、BA、QA、交付团队的探索、规划、细化及就绪成果物放在
    specs-refiniment/<feature-name>/<file.md>
    路径下。
  • 使用路径模式
    specs-refiniment/<feature-name>/<file.md>
    ;若已知稳定的功能别名则使用,否则
    <feature-name>
    使用
    tbd-<short-topic>
  • 不得将该技能的输出写入
    specs/
    文件夹;该文件夹专为开发人员的实施SDD成果物保留。
  • 若用户明确要求将细化后的成果物转换为开发人员实施工作,需交接给
    $ai-sdlc-sdd

0.5 Feature State Machine

0.5 功能状态机

  • Maintain feature lifecycle state in TOON at
    specs-refiniment/<feature-name>/_ai_sdlc/state.toon
    for refinement work and
    specs/<feature-name>/_ai_sdlc/state.toon
    for implementation work.
  • Before executing this skill for a feature, check the state machine with
    python3 skills/_shared/state_machine.py check --feature <feature-name> --skill <this-skill-name> --workspace <refinement|implementation> --quick-flow|--full-flow
    .
  • When this skill starts durable work, mark it in progress with
    begin
    ; when the skill's required artifact or review is complete, mark it done with
    complete
    and include
    --artifacts <path>
    plus
    --decision-ref DEC-###
    when a decision was involved.
  • In
    --full-flow
    , do not proceed when predecessor stages are incomplete, another lifecycle skill is active, or the state file reports a blocker.
  • In
    --quick-flow
    , a predecessor skip is allowed only when continuing is low risk and the command includes
    --assumption "..."
    or
    --decision-ref DEC-###
    ; record the same assumption or decision in
    decision-log.md
    .
  • Use
    python3 skills/_shared/state_machine.py status --feature <feature-name> --workspace <refinement|implementation> --format toon
    to emit compact LLM-readable state before choosing the next skill.
  • The state machine is feature-scoped: do not reuse a
    state.toon
    across unrelated feature folders.
  • 在TOON中维护功能生命周期状态:细化工作的状态存于
    specs-refiniment/<feature-name>/_ai_sdlc/state.toon
    ,实施工作的状态存于
    specs/<feature-name>/_ai_sdlc/state.toon
  • 在为某个功能执行该技能前,使用
    python3 skills/_shared/state_machine.py check --feature <feature-name> --skill <this-skill-name> --workspace <refinement|implementation> --quick-flow|--full-flow
    检查状态机。
  • 当该技能开始持久化工作时,用
    begin
    标记为进行中;当技能所需的成果物或评审完成时,用
    complete
    标记为已完成,若涉及决策需添加
    --artifacts <path>
    --decision-ref DEC-###
  • --full-flow
    模式下,当前置阶段未完成、另一个生命周期技能处于活跃状态或状态文件报告阻塞时,不得继续推进。
  • --quick-flow
    模式下,仅当继续推进风险低且命令包含
    --assumption "..."
    --decision-ref DEC-###
    时,才允许跳过前置阶段;需在
    decision-log.md
    中记录相同的假设或决策。
  • 使用
    python3 skills/_shared/state_machine.py status --feature <feature-name> --workspace <refinement|implementation> --format toon
    输出紧凑的LLM可读状态,再选择下一个技能。
  • 状态机以功能为范围:不得在不相关的功能文件夹间复用
    state.toon

0.6 Artifact Metadata And Metatags

0.6 成果物元数据与元标签

  • Every Markdown artifact generated or updated by this skill must start with an
    artifact_metadata
    YAML frontmatter block before the first visible heading.
  • Use schema
    ai-sdlc-artifact-metadata/v1
    and keep these fields current:
    feature
    ,
    artifact
    ,
    path
    ,
    workspace
    ,
    skill
    ,
    flow_mode
    ,
    state_file
    ,
    decision_log
    ,
    status
    ,
    owner
    ,
    created_at
    ,
    updated_at
    ,
    trace_ids
    ,
    related_artifacts
    ,
    validation
    , and
    metatags
    .
  • metatags
    must include at minimum
    ai-sdlc
    , the workspace (
    refinement
    or
    implementation
    ), this skill name, the artifact type or filename stem, and a lifecycle/status tag such as
    draft
    ,
    review
    ,
    approved
    , or
    validated
    .
  • When
    --quick-flow
    is active, set
    flow_mode: quick
    , keep assumptions visible in the body, and add tags for major defaults or unresolved risk only when they help retrieval.
  • When
    --full-flow
    is active, set
    flow_mode: full
    , keep blockers and validation evidence reflected in
    status
    ,
    validation
    ,
    trace_ids
    , and
    related_artifacts
    .
  • Update metadata whenever the artifact path, status, owner, trace links, validation evidence, related artifacts, or decision references change.
  • Metadata is an index for routing, retrieval, and traceability; it does not replace the artifact body,
    decision-log.md
    , or
    state.toon
    .
  • 该技能生成或更新的每个Markdown成果物,必须在第一个可见标题前添加
    artifact_metadata
    YAML前置块。
  • 使用
    ai-sdlc-artifact-metadata/v1
    schema,并保持以下字段最新:
    feature
    artifact
    path
    workspace
    skill
    flow_mode
    state_file
    decision_log
    status
    owner
    created_at
    updated_at
    trace_ids
    related_artifacts
    validation
    metatags
  • metatags
    至少需包含
    ai-sdlc
    、工作区(
    refinement
    implementation
    )、该技能名称、成果物类型或文件名主干,以及生命周期/状态标签(如
    draft
    review
    approved
    validated
    )。
  • --quick-flow
    激活时,设置
    flow_mode: quick
    ,在正文中显示假设,仅当有助于检索时才添加主要默认值或未解决风险的标签。
  • --full-flow
    激活时,设置
    flow_mode: full
    ,在
    status
    validation
    trace_ids
    related_artifacts
    中反映阻塞点和验证证据。
  • 当成果物路径、状态、负责人、追溯链接、验证证据、关联成果物或决策引用发生变化时,需更新元数据。
  • 元数据是用于路由、检索和可追溯性的索引;不得替代成果物正文、
    decision-log.md
    state.toon

0.7 Specs Index

0.7 规格说明索引

  • Before searching across feature folders, inspect the compact LLM index first:
    specs-refiniment/_ai_sdlc/specs-index.toon
    for refinement work or
    specs/_ai_sdlc/specs-index.toon
    for implementation work.
  • Use the human-readable index at
    specs-refiniment/specs-index.md
    or
    specs/specs-index.md
    when reporting feature coverage, artifact inventory, or handoff status to people.
  • After this skill creates or materially updates an artifact, refresh the matching workspace index with
    python3 skills/_shared/ai_sdlc_specs_index.py --workspace <refinement|implementation> --quick-flow|--full-flow
    .
  • In
    --quick-flow
    , rely on
    specs-index.toon
    to choose the smallest relevant artifact set before opening files.
  • In
    --full-flow
    , verify the updated artifact appears in both
    specs-index.toon
    and
    specs-index.md
    before final handoff.
  • The specs index summarizes artifact metadata and state; it does not replace reading the selected source artifacts when details, approvals, or validation evidence matter.
  • 在跨功能文件夹搜索前,先查看紧凑的LLM索引:细化工作的索引为
    specs-refiniment/_ai_sdlc/specs-index.toon
    ,实施工作的索引为
    specs/_ai_sdlc/specs-index.toon
  • 当向人员报告功能覆盖范围、成果物清单或交接状态时,使用人类可读索引
    specs-refiniment/specs-index.md
    specs/specs-index.md
  • 该技能创建或大幅更新成果物后,使用
    python3 skills/_shared/ai_sdlc_specs_index.py --workspace <refinement|implementation> --quick-flow|--full-flow
    刷新匹配的工作区索引。
  • --quick-flow
    模式下,依赖
    specs-index.toon
    选择最小的相关成果物集,再打开文件。
  • --full-flow
    模式下,在最终交接前验证更新后的成果物是否同时出现在
    specs-index.toon
    specs-index.md
    中。
  • 规格说明索引总结成果物元数据和状态;当细节、审批或验证证据重要时,不得替代阅读选定的源成果物。

0.8 Complete Refinement Cascade

0.8 完整细化流程

  • Trigger the complete cascade only when the user explicitly asks for a full, complete, or end-to-end spec refinement or asks for every refinement artifact. A normal
    --full-flow
    call for one skill remains single-stage.
  • Before the first durable write, run
    python3 skills/_shared/refinement_status.py --feature <feature-name> --gate full --format toon
    and start with the earliest reported
    next_skill
    , including stages earlier than this skill.
  • Execute the existing refinement skills in lifecycle order with
    --full-flow
    : discovery, PRFAQ, delivery-package gap review, requirements readiness, goal/capability mapping, backlog gap review, backlog decomposition, story decomposition, release slicing, BA context, delivery spec, QA plan, QA gap review, test strategy, test cases, test suite, QA readiness, and delivery handoff.
  • Produce all 18 canonical Markdown artifacts.
    release-slicing.md
    is mandatory for a complete cascade; when release slicing is not applicable, write an explicit evidence-backed N/A artifact and complete the stage instead of skipping it.
  • After every stage, finalize its artifact, record required decisions, mark the stage
    done
    , and refresh the refinement indexes before selecting the next skill.
  • Do not declare the cascade complete until
    python3 skills/_shared/refinement_status.py --feature <feature-name> --gate full --format markdown
    exits successfully with
    18/18
    . If it fails, continue with the reported next skill or return the concrete blocker and remaining inventory in Codex.
  • Surface checkpoint and final summaries in Codex only; never persist a cascade summary as a text file.
  • 仅当用户明确要求完整、全面或端到端的规格说明细化,或要求所有细化成果物时,才触发完整流程。正常的
    --full-flow
    单技能调用仍为单阶段。
  • 在第一次持久化写入前,运行
    python3 skills/_shared/refinement_status.py --feature <feature-name> --gate full --format toon
    ,从报告的最早
    next_skill
    开始,包括早于该技能的阶段。
  • 按生命周期顺序使用
    --full-flow
    执行现有细化技能:探索、PRFAQ、交付包缺口评审、需求就绪度、目标/能力映射、待办事项缺口评审、待办事项分解、需求故事分解、发布切片、BA上下文、交付规格说明、QA计划、QA缺口评审、测试策略、测试用例、测试套件、QA就绪度及交付交接。
  • 生成全部18个标准Markdown成果物。
    release-slicing.md
    是完整流程的必填项;若发布切片不适用,需写入明确的基于证据的N/A成果物并完成该阶段,不得跳过。
  • 每个阶段完成后,最终确定其成果物、记录必需的决策、将阶段标记为
    done
    ,并在选择下一个技能前刷新细化索引。
  • 仅当
    python3 skills/_shared/refinement_status.py --feature <feature-name> --gate full --format markdown
    成功退出且显示
    18/18
    时,才可宣布流程完成。若失败,继续执行报告的下一个技能,或在Codex中返回具体阻塞点及剩余清单。
  • 仅在Codex中显示检查点和最终摘要;不得将流程摘要持久化为文本文件。

References

参考资料

  • Use
    scripts/handoff_readiness_score.py
    when deterministic scaffolding, planning, or formatting is useful for this workflow; pass the same
    --quick-flow
    or
    --full-flow
    flag that was supplied to the skill.
  • Read
    references/handoff-checklist.md
    when the task needs the detailed structure, checklist, or examples for this skill.
  • 当该工作流需要确定性脚手架、规划或格式化时,使用
    scripts/handoff_readiness_score.py
    ;传入与技能相同的
    --quick-flow
    --full-flow
    标识。
  • 当任务需要该技能的详细结构、检查清单或示例时,阅读
    references/handoff-checklist.md

Script Usage

脚本使用

  • In default and full flow, always run this skill's primary analysis script with
    --format toon --budget-tokens 24000
    before drafting; explicit inputs are priority evidence but do not replace the rest of the feature package.
  • Read this skill's reference file before writing sections. Use its detailed tables and quality bar, not only the compact scaffold headings.
  • Run the primary script with
    --emit-template
    in the active flow mode to obtain the exact shared context headings and required stage table columns before section writes.
  • Make every default/full artifact self-contained by completing all ten shared feature-context sections plus the stage-specific profile sections. Quick flow may use the compact stage-only draft.
  • Follow every
    next_reads
    entry before finalization and list every consumed source in
    Source Coverage
    ; do not claim whole-feature context from a partial source set.
  • Keep the final artifact within
    --max-artifact-tokens 24000
    ; condense repetition instead of dropping feature dimensions or source traceability.
  • Run
    scripts/handoff_readiness_score.py
    before drafting or updating this skill's artifact when inputs are longer than a few bullets, when traceability matters, or when a flow flag is supplied. For agent analysis, pass
    --format toon
    , read
    anchors
    first, and open only
    next_reads
    ; without that flag the script keeps its human-readable Markdown output.
  • Quick flow analysis:
    python3 skills/ai-sdlc-delivery-handoff-review/scripts/handoff_readiness_score.py --feature <feature-name> --quick-flow <input.md>...
  • Full flow analysis:
    python3 skills/ai-sdlc-delivery-handoff-review/scripts/handoff_readiness_score.py --feature <feature-name> --full-flow <input.md>...
  • To write content, pass one canonical heading with
    --section "<section>"
    ; provide only that section body on stdin, without H1, H2, frontmatter, or a temporary content file.
  • Repeat
    --section
    for each required section, then run the same script with
    --finalize
    to validate the artifact and refresh metadata and specs indexes.
  • The AI must not write or directly edit the routed Markdown artifact; the script owns scaffold creation, section placement, and durable file writes.
  • Use
    --decision-row
    with one nine-cell Markdown table row on stdin when a decision-log entry is required.
  • Legacy
    --emit-template
    ,
    --emit-decision-log-entry
    , and
    --write
    remain available for compatibility.
  • Use
    --quick-flow
    for first-pass synthesis with assumptions; use
    --full-flow
    before readiness, handoff, signoff, or any decision-sensitive output.
  • 在默认和完整流程中,起草前始终使用
    --format toon --budget-tokens 24000
    运行该技能的主分析脚本;明确输入是优先证据,但不能替代整个功能包。
  • 写入章节前阅读该技能的参考文件。使用其详细表格和质量标准,而非仅使用紧凑的脚手架标题。
  • 在当前流程模式下运行主脚本并添加
    --emit-template
    ,以获取精确的共享上下文标题和必需的阶段表格列,再进行章节写入。
  • 每个默认/完整成果物需包含全部十个共享功能上下文章节及阶段特定配置文件章节,确保自包含。快速流程可使用紧凑的仅阶段草稿。
  • 完成前遵循每个
    next_reads
    条目,并在
    Source Coverage
    中列出所有使用的源;不得从部分源集声称拥有完整功能上下文。
  • 最终成果物需控制在
    --max-artifact-tokens 24000
    范围内;精简重复内容,不得省略功能维度或源可追溯性。
  • 当输入超过几个项目符号、可追溯性重要或提供了流程标识时,起草或更新该技能的成果物前需运行
    scripts/handoff_readiness_score.py
    。对于Agent分析,传入
    --format toon
    ,先读取
    anchors
    ,再打开仅
    next_reads
    ;若不使用该标识,脚本将保留人类可读的Markdown输出。
  • 快速流程分析:
    python3 skills/ai-sdlc-delivery-handoff-review/scripts/handoff_readiness_score.py --feature <feature-name> --quick-flow <input.md>...
  • 完整流程分析:
    python3 skills/ai-sdlc-delivery-handoff-review/scripts/handoff_readiness_score.py --feature <feature-name> --full-flow <input.md>...
  • 若要写入内容,传入一个标准标题并添加
    --section "<section>"
    ;仅在标准输入中提供该章节正文,不得包含H1、H2、前置块或临时内容文件。
  • 对每个必需章节重复
    --section
    ,然后使用
    --finalize
    运行相同脚本,以验证成果物并刷新元数据和规格说明索引。
  • AI不得直接写入或编辑路由的Markdown成果物;脚本负责脚手架创建、章节放置及持久化文件写入。
  • 当需要决策日志条目时,使用
    --decision-row
    并在标准输入中提供一行九单元格的Markdown表格。
  • 旧版
    --emit-template
    --emit-decision-log-entry
    --write
    仍可兼容使用。
  • 使用
    --quick-flow
    进行带假设的首次整合;在就绪度检查、交接、签署或任何决策敏感输出前使用
    --full-flow

Purpose

目的

Run the final quality gate on the delivery package before it is treated as ready for implementation planning or handoff.
在交付包被认定为可进入实施规划或交接阶段前,运行最终质量gate进行检查。

Use When

使用场景

  • Stories and spec are complete enough to review as a package.
  • The team needs an explicit judgment on readiness and remaining risk.
  • 需求故事和规格说明已足够完整,可作为一个包进行评审。
  • 团队需要对就绪度和剩余风险做出明确判断。

Do Not Use When

禁用场景

  • The delivery gap review or decomposition work is still incomplete.
  • The package does not yet contain both stories and a structured spec.
  • 交付缺口评审或分解工作仍未完成。
  • 包中尚未同时包含需求故事和结构化规格说明。

Workflow

工作流程

  1. Compare the input package, stories, and spec for consistency.
  2. Check coverage of actors, workflows, edge cases, dependencies, business rules, and open questions.
  3. Identify what still blocks confident delivery handoff.
  4. Assign a readiness score and explain the reasons.
  5. State what must be clarified next before implementation starts.
  1. 比较输入包、需求故事和规格说明的一致性。
  2. 检查参与者、工作流、边缘情况、依赖关系、业务规则及未解决问题的覆盖情况。
  3. 识别仍会阻碍交付交接信心的因素。
  4. 分配就绪度评分并说明理由。
  5. 说明实施开始前必须澄清的事项。

Review Rules

评审规则

  • Be strict.
  • Block handoff if stories and spec contradict each other.
  • Block handoff if acceptance criteria are not testable.
  • Block handoff if critical dependencies or decisions remain hidden.
  • Distinguish between non-blocking gaps and true delivery blockers.
  • 严格执行。
  • 若需求故事与规格说明存在矛盾,阻止交接。
  • 若验收标准不可测试,阻止交接。
  • 若关键依赖关系或决策仍未明确,阻止交接。
  • 区分非阻塞性缺口与真正的交付阻塞点。

Checklist

检查清单

Use
references/handoff-checklist.md
.
使用
references/handoff-checklist.md

Completion Criteria

完成标准

  • The review identifies concrete strengths and blockers.
  • The readiness score is justified.
  • Remaining questions are actionable.
  • The recommendation is clear enough for delivery planning.
  • 评审明确指出具体优势和阻塞点。
  • 就绪度评分具备合理性。
  • 剩余问题具备可操作性。
  • 建议足够清晰,可用于交付规划。