Evidence snapshot reviewed Sep 5, 2026GitHub checked Aug 21, 2026
Source-reviewedStandalone SkillCoding & ReviewCoding & Review Profile

evaluate

Evaluate an execution session with mechanical checks, semantic review, and optional multi-model consensus.

At a glance

What it does

Evaluate an execution session with mechanical checks, semantic review, and optional multi-model consensus.

Capabilities
Coding & ReviewCode ReviewTestingWorkflow Automation

Before you choose it

This Ouroboros skill evaluates a session or specified artifact in three progressive stages. It first fails fast on mechanical validation such as linting, builds, tests, static analysis, and coverage; then assesses acceptance-criteria compliance, goal alignment, and drift. When uncertainty remains or you request it, it can add a majority-vote multi-model review.

Best for

Developers using Ouroboros who need an evidence-based approval or rejection of a completed execution session.

Common tasks

  • Check whether a recent coding session passes build, test, and lint validation.
  • Assess whether an artifact meets its acceptance criteria and intended goal.
  • Request an optional multi-model consensus when a semantic verdict is uncertain.

Permissions and data

Uses Ouroboros MCP evaluation tools when available and may inspect supplied artifacts and execution-session context.

Permissions
  • May invoke MCP evaluation tools after runtime tool discovery.
  • May read a user-specified artifact or recent execution output.
  • May run mechanical validation commands when the runtime exposes acting tools.
Data handling
  • Evaluation inputs can include session IDs, artifacts, observed command output, and acceptance criteria.
External services
  • Optional multi-model consensus is used only for Stage 3 when uncertainty or a manual request triggers it.
Credentials
  • No credential requirement is declared in the supplied skill document; availability depends on the Ouroboros MCP server or evaluator agent.

Limitations

  • No Harness version range is declared in the supplied evidence.
  • The optional multi-model consensus is not a default stage.
  • If the Ouroboros MCP server is unavailable, results come from a qualitative evaluator-agent fallback rather than the MCP pipeline.

What DSHub checked

  • The pinned skill document was captured and the immutable source check passed.
  • The supplied repository evidence identifies an MIT license.

What DSHub did not check

  • This candidate was not installed or run by DSHub.
  • Runtime availability of the Ouroboros MCP tools was not verified.

Pinned install

Primary action

This standalone skill does not have a DSH Plugin install action. Use its source documentation for the delivery method.

Visit the source project

Maintainer source

Skill instructions

View at commit 03714ba
Maintainer-authored contentCaptured from skills/evaluate/SKILL.md on Sep 5, 2026. The text and repository-relative media are fixed to commit 03714ba44618 with content hash f3a8d30d5cf0; provider-hosted badges may update independently. SKILL.md commands are upstream documentation; use the type-correct primary action above and verify it against this pinned source.

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.

Operate deliberately

Install and manage

Prerequisites and target Profile

Target Coding & Review Profile

Delivery Skill Files — https://raw.githubusercontent.com/Q00/ouroboros/03714ba446186423dcb46e25d12bd19c3a2e82f6/skills/evaluate/SKILL.md

Compatibility and access

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

Review compatibility evidence

Risk facts

Command Execution

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

Evidence
External Models

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

Evidence
Evidence and editorial reviewManifest, Bundle patch, distribution and freshness

Immutable evidence

Review status and source activity

Human approved

Approved for publication after reviewing the source-linked content and immutable release record. AI assisted with the draft; the publication decision was human.

Human reviewed Sep 5, 2026, 5:17 PM UTCGitHub facts last checked Sep 5, 2026, 4:31 PM UTC

No material source change has been recorded since this evidence baseline.

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