证据快照复核于 2026-09-05GitHub 数据核对日期: 2026-08-21
来源已审查独立 Skill编码与审查编码与审查 Profile

evaluate

通过机械检查、语义审查和可选多模型共识评估一次执行会话。

快速了解

它能做什么

通过机械检查、语义审查和可选多模型共识评估一次执行会话。

本站提供的是中文说明,不代表该项目或 Plugin 自身提供中文界面;语言支持请以上游文档为准。

能力
编码与审查代码审查测试工作流自动化

选择前先看

该 Ouroboros 技能会按三个递进阶段评估会话或指定产物:先对 lint、构建、测试、静态分析和覆盖率等进行快速机械验证,再评估验收标准符合度、目标对齐度和偏离程度;如存在不确定性或你明确要求,还会加入多模型多数表决。

适合谁

需要对已完成执行会话作出有依据的通过或拒绝判断的 Ouroboros 开发者。

常见任务

  • 确认最近一次编码会话是否通过构建、测试和 lint 验证。
  • 评估某个产物是否符合验收标准与预期目标。
  • 当语义结论不明确时,请求可选的多模型共识评审。

权限与数据

在可用时使用 Ouroboros MCP 评估工具,并可能读取所提供的产物和执行会话上下文。

权限
  • 可在运行时工具发现后调用 MCP 评估工具。
  • 可读取用户指定的产物或最近的执行输出。
  • 当运行环境提供操作工具时,可运行机械验证命令。
数据处理
  • 评估输入可能包含会话 ID、产物、已观察到的命令输出和验收标准。
外部服务
  • 仅在第三阶段因不确定性或手动请求触发时使用可选的多模型共识。
凭据
  • 提供的技能文档未声明凭证要求;可用性取决于 Ouroboros MCP 服务器或 evaluator agent。

局限

  • 提供的证据未声明 Harness 版本范围。
  • 多模型共识是可选阶段,并非默认执行。
  • 如果 Ouroboros MCP 服务器不可用,将使用定性 evaluator agent 回退方案,而非 MCP 流水线。

DSHub 已核对

  • 已捕获固定版本的技能文档,且不可变来源检查已通过。
  • 提供的仓库证据表明其采用 MIT 许可证。

DSHub 未核对

  • DSHub 未安装或运行该候选项。
  • 未验证运行环境中 Ouroboros MCP 工具是否可用。

固定版本安装

主要操作

这个独立 Skill没有 DSH Plugin 安装操作,请根据源码文档使用真实交付方式。

访问源码项目

维护者原文

Skill 使用说明

查看 commit 03714ba 对应的 SKILL.md
维护者编写的上游内容原文于 2026/9/5skills/evaluate/SKILL.md 获取,正文和仓库相对媒体固定到 commit 03714ba44618,内容哈希为 f3a8d30d5cf0。以下是未经 DSHub 翻译的上游原文,语言可能与当前页面不同;第三方托管的 badge 可能独立更新。

name: evaluate description: "Evaluate execution with three-stage verification pipeline" aliases: [eval]

/ouroboros:evaluate

Evaluate an execution session using the three-stage verification pipeline.

Usage

/ouroboros:evaluate <session_id> [artifact]

Trigger keywords: "evaluate this", "3-stage check"

How It Works

The evaluation pipeline runs three progressive stages:

  1. Stage 1: Mechanical Verification ($0 cost)

    • Lint checks, build validation, test execution
    • Static analysis, coverage measurement
    • Fails fast if mechanical checks don't pass
  2. Stage 2: Semantic Evaluation (Standard tier)

    • AC compliance assessment
    • Goal alignment scoring
    • Drift measurement
    • Reasoning explanation
  3. Stage 3: Multi-Model Consensus (Frontier tier, optional)

    • Multiple models vote on approval
    • Only triggered by uncertainty or manual request
    • Majority ratio determines outcome

Instructions

When the user invokes this skill:

Load MCP Tools (Required first)

The Ouroboros MCP tools are often registered as deferred tools that must be explicitly loaded before use. You MUST perform this step before proceeding.

  1. Use the active runtime's tool-discovery capability to find and load the evaluate MCP tools:
    tool discovery query: "+ouroboros evaluate"
    
  2. The tool will typically be named mcp__plugin_ouroboros_ouroboros__ouroboros_start_evaluate (with a plugin prefix). After runtime tool discovery returns, the tool becomes callable.
  3. If the tool is callable — already exposed, or loaded by discovery — proceed with the MCP-based evaluation below. An empty discovery result for an already-exposed tool is expected, not a failure. Skip to the Fallback section only if the tool is genuinely absent (no Ouroboros MCP server).

IMPORTANT: Do NOT skip this step. Do NOT assume MCP tools are unavailable just because they don't appear in your immediate tool list. They are almost always available as deferred tools that need to be loaded first.

CRITICAL — deferred-schema guard (prevents "Invalid tool parameters"): This skill can call ouroboros_start_evaluate after a fresh turn. A deferred tool's schema loaded on one turn is NOT guaranteed to still be loaded on the next. If you call it while its schema is not loaded in the current turn, the runtime rejects the call with "Invalid tool parameters" before it reaches the server. Therefore: immediately before EVERY ouroboros_start_evaluate call in this skill, re-run tool discovery query: "+ouroboros evaluate" (idempotent — a no-op when already loaded). If the load returns no matching tool (and the tool is not already callable — an empty load for an already-exposed tool is an expected no-op, not absence), switch to the documented fallback instead of retrying the failing call.

Evaluation Steps

  1. Determine what to evaluate:

    • If session_id provided: Use it directly
    • If no session_id: Check conversation for recent execution session IDs
  2. Gather the artifact to evaluate:

    • If user specifies a file: Read it with Read tool
    • If recent execution output exists in conversation: Use that
    • Ask user if unclear what to evaluate

2.5. Acting verification — reproduce and OBSERVE (do not skip for behaviour-bearing work): Stage 1 already runs mechanical checks (build/test). Go further when the runtime exposes acting tools — computer-use / browser, Bash/shell, file reads: don't just reason over the diff, run the result and observe the real effect (the command's output, the endpoint's response, the rendered UI via a screenshot). Do it via a dedicated verification sub-agent to keep the main session lean — or inline in the main session where the runtime restricts sub-agent spawning (the observation is what matters; the delegation is only an optimization). Probe the acceptance criteria against the ACTUAL observable behaviour and the adversarial classes (misleading_output, hung_command, stale_state, dirty_worktree, …). Feed the captured evidence (commands, outputs, artifact paths) into the evaluate call as part of the artifact. If acting tools are unavailable, note that behaviour was not observed and evaluate on the text alone.

  1. Call the background ouroboros_start_evaluate MCP tool so rejected verdicts can continue through the configured Ralph convergence chain:

    Tool: ouroboros_start_evaluate
    Arguments:
      session_id: <session ID>
      artifact: <the code/output to evaluate, plus observed-behaviour evidence from 2.5>
      seed_content: <original seed YAML, if available>
      acceptance_criterion: <specific AC to check, optional>
      artifact_type: "code"  (or "docs", "config")
      working_dir: <absolute project root, recommended>
      trigger_consensus: false  (true if user requests Stage 3)
      auto_evolve: <optional override; omit to use execution.auto_evolve>
    

    working_dir controls both Stage 1 command execution and Stage 2 source-file visibility. Pass the absolute project root whenever available; if omitted, the MCP handler falls back to the registered brownfield default, seed project metadata, then the MCP server cwd.

  2. Observe the returned evaluation job. If its terminal result contains chained_ralph_job_id, follow that Ralph job to terminal before presenting the convergence outcome. A missing Seed produces chained_ralph_skipped: seed_unavailable; preserve the rejected verdict and explain that automatic continuation was safely skipped. In OpenCode plugin mode, auto_evolve=true intentionally returns this pollable parent-owned job; with automatic evolution disabled, the plugin child remains the terminal surface and job_id is None.

  3. Present results clearly:

    • Show each stage's pass/fail status
    • Highlight the final approval decision
    • If rejected, explain the failure reason
    • Suggest fixes if evaluation fails
    • Always end with a state breadcrumb based on the outcome:
      • APPROVED: ◆ Evaluation approved → next: accept, or ooo evolve to iteratively refine
      • REJECTED at Stage 1 (mechanical, code_changes_detected: true): ◆ Current state → next: Fix the build/test failures above, then ooo evaluate — or ooo ralph for automated fix loop
      • REJECTED at Stage 1 (mechanical, code_changes_detected: false): ◆ Current state → next: Run ooo run first to produce code, then ooo evaluate
      • REJECTED at Stage 2 (semantic): ◆ Current state → next: ooo run to re-execute with fixes — or ooo evolve for iterative refinement
      • REJECTED at Stage 3 (consensus): ◆ Current state → next: ooo interview to re-examine requirements — or ooo unstuck to challenge assumptions

Fallback (No MCP Server)

If the MCP server is not available, use the ouroboros:evaluator agent to perform a prompt-based evaluation:

  1. Delegate to ouroboros:evaluator agent
  2. The agent performs qualitative evaluation based on the seed spec
  3. Results are advisory (no numerical scoring without Python core)

Example

User: /ouroboros:evaluate sess-abc-123

Evaluation Results
============================================================
Final Approval: APPROVED
Highest Stage Completed: 2

Stage 1: Mechanical Verification
  [PASS] lint: No issues found
  [PASS] build: Build successful
  [PASS] test: 12/12 tests passing

Stage 2: Semantic Evaluation
  Score: 0.85
  AC Compliance: YES
  Goal Alignment: 0.90
  Drift Score: 0.08

◆ Evaluation approved → next: accept, or `ooo evolve` to iteratively refine

RFC #1392 State Breadcrumb Footer

Your final response MUST end with exactly one breadcrumb footer line:

◆ <current state> → next: <recommended action>

Derive <current state> from live session state via ouroboros_session_status when that MCP projection is available; otherwise derive it from this skill's actual outcome. Never use a linear Step N of M footer because Ouroboros is an evolutionary loop. When the next action is genuinely a choice, list 2-3 honest options in the next: clause. The breadcrumb line must be the last line of the response.

有意识地管理

安装与管理

前置条件与目标 Profile

目标 编码与审查 Profile

交付方式 Skill 文件 — https://raw.githubusercontent.com/Q00/ouroboros/03714ba446186423dcb46e25d12bd19c3a2e82f6/skills/evaluate/SKILL.md

兼容性与访问范围

Requires an Ouroboros MCP server or evaluator-agent fallback Not declared in supplied evidence

检查兼容性证据

风险事实

command-execution

Stage 1 can run lint, build, test, static-analysis, and coverage checks.

证据
external-models

Optional Stage 3 sends work through a multi-model approval consensus.

证据
证据与编辑审查Manifest、Bundle patch、分发与新鲜度

不可变证据

审查状态与源码活动

人工已批准

在核对来源内容和不可变发布记录后,已由人工批准发布。AI 参与了内容草稿生成,最终发布决定由人工完成。

人工审查于 2026/9/5 UTC 17:17GitHub 事实核对日期: 2026/9/5 UTC 16:31

自当前证据基线以来,没有记录到重要源码变化。

下一步

比较生态 Artifact 类型

订阅重要变化: evaluate