agent-evaluation-framework
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Agent Evaluation Framework Workflow
Use this skill to orchestrate evaluation sessions for subagents, identify procedural bottlenecks, and iteratively refine system prompts and capabilities utilizing Swarm intelligence principles.
0. Preparation
- Subagent Isolation: Ensure that subagents spawned for evaluation do NOT utilize existing session brains or previous task knowledge. This is critical to maintain the integrity of meta-testing.
- Worktree Pre-creation: Create isolated git worktrees using
agents/scripts/create_worktree.sh <task_id>for each test case beforehand. Report where the worktrees were created to the user. Inside worktrees, builds MUST use thetools/dev/gm.pytool INSIDE the worktree.gm.pywill automatically runsetup_worktree_build.pyto prepare the symlinks; manual execution ofsetup_worktree_build.pyis not required. - Test Injection: Copy the target test case into the worktree (e.g.,
test/mjsunit/repro.js). - Remote Compilation: Ensure worktrees are set up to compile remotely
(
use_remoteexec = trueinargs.gn) before proceeding.
1. Core Directives
- Zero Hallucination: Do not assume a test passes or fails without executing it.
- Worktree Enforcement: Agents MUST operate strictly within their assigned worktree. They should NOT know the main V8 root exists.
- Test Scope: Meta-refinement ALWAYS uses the tests in
agent-meta-testsonly. - Test Immutability: The
agent-meta-testsdirectory cannot be changed. - Crash Verification: Only work on test-cases that still crash.
- Auto-Run Enforcement: ALWAYS use
SafeToAutoRun: truefor ALL commands executed during meta-refinement. Approval must NEVER be asked of the user. - Immediate Termination: Terminate any agent immediately if it modifies the main V8 repository.
2. Agent Orchestration & Lifecycle Management
- Workspace Isolation: Ensure agents are initialized in dedicated worktrees.
- Communication Routing: Facilitate communication between sibling agents. Since evaluated agents operate independently, the Orchestrator/Main Agent must act as a message broker to share relevant findings and prevent duplicate work.
- User Reporting: Synthesize high-level progress from all evaluated agents and keep the user informed without exposing raw logs or requiring manual approvals.
3. Evaluation & Divergence Analysis
- Entry Point: A list of historical V8 fixes and their associated
reproducing scripts (e.g., from
test/mjsunit/or Buganizer). - Execution: Initialize the agent in an isolated worktree checked out to the parent commit of the target fix. Copy the repro script and command the agent to resolve the bug.
- Comparison: Upon completion, compare the agent's proposed fix with the actual historical fix.
- Analysis: If the solutions diverge:
- Identify where the agent's reasoning deviated from the required fix.
- Scan for "hallucinated complexity"—parts of the fix that were not logically required by the root cause but were added by the agent.
- Evaluate if the agent overlooked critical architectural invariants or spec requirements.
- Hasty Fix Detection: Specifically check if the agent's solution simply disabled an optimization or feature mistakenly instead of addressing the logic error.
- Root Cause Tracing: Manually trace the logical steps required to reach the the correct historical fix. Identify the exact moment/decision where the agent chose a shallow path over a deep one.
4. Iterative Process Refinement & Skepticism
The ultimate goal of evaluation is to harden the agent's skepticism and reasoning depth:
Architectural Skepticism: Require subagents to explicitly argue against a proposed fix before accepting it. Look at the problem from multiple orthogonal angles.
Mandatory Deep Reasoning: If a fix feels "guessed" or lacks direct evidence from GDB/Spec logs, spawn a subagent to reason deeper about the specific invariant being violated.
Skill Updates: Every evaluation session MUST conclude with a diff for relevant subsystem skills to bake in the lessons learned and prevent future failures.
analyze_brain.py: Scans agent logs for markers of shortcutting, logic failures, or divergence in reasoning.
- Fluxly category
- Design
- Author-declared agents
- No explicit declaration found; this is not inferred or tested compatibility
- Static check
- 88 / 100 · heuristic scan, not runtime safety proof
- Author / version / license
- @v8 · no license declared
- Fluxly token estimate
- Lean
- Fluxly setup estimate
- Guided setup
- External API key
- No requirement detected
- Detected OS requirements
- Unspecified
- Runtime requirements
- Unspecified
- Detected file/system behavior
-
- Read-only
- Write / modify
- Shell exec
- Detected network behavior
- Local-only
- Install commands
- None (reference only)
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
The current SKILL.md does not define a fixed output example. Subagent Isolation: Ensure that subagents spawned for evaluation do NOT utilize existing session brains or previous task knowledge. This is critical to maintain the integrity of meta-testing.
Zero Hallucination: Do not assume a test passes or fails without executing it. Worktree Enforcement: Agents MUST operate strictly within their assigned
Workspace Isolation: Ensure agents are initialized in dedicated worktrees. Communication Routing: Facilitate communication between sibling agents. Since evaluated agents operate independently, the Orchestrator/Main Agent must
Entry Point: A list of historical V8 fixes and their associated reproducing scripts (e.g., from test/mjsunit/ or Buganizer). Execution: Initialize the agent in an isolated worktree checked out to the
The ultimate goal of evaluation is to harden the agent's skepticism and reasoning depth: Architectural Skepticism: Require subagents to explicitly argue against
# Agent Evaluation Framework Workflow
Use this skill to orchestrate evaluation sessions for subagents, identify
procedural bottlenecks, and iteratively refine system prompts and capabilities
utilizing Swarm intelligence principles.
## 0. Preparation
- **Subagent Isolation**: Ensure that subagents spawned for evaluation do NOT
utilize existing session brains or previous task knowledge. This is critical
to maintain the integrity of meta-testing.
- **Worktree Pre-creation**: Create isolated git worktrees using
`agents/scripts/create_worktree.sh <task_id>` for each test case beforehand.
Report where the worktrees were created to the user. Inside worktrees, builds
MUST use the `tools/dev/gm.py` tool INSIDE the worktree. `gm.py` will
automatically run `setup_worktree_build.py` to prepare the symlinks; manual
execution of `setup_worktree_build.py` is not required.
- **Test Injection**: Copy the target test case into the worktree (e.g.,
`test/mjsunit/repro.js`).
- **Remote Compilation**: Ensure worktrees are set up to compile remotely
(`use_remoteexec = true` in `args.gn`) before proceeding.
## 1. Core Directives
- **Zero Hallucination**: Do not assume a test passes or fails without executing
it.
- **Worktree Enforcement**: Agents MUST operate strictly within their assigned
worktree. They should NOT know the main V8 root exists.
- **Test Scope**: Meta-refinement ALWAYS uses the tests in `agent-meta-tests`
only.
- **Test Immutability**: The `agent-meta-tests` directory cannot be changed.
- **Crash Verification**: Only work on test-cases that still crash.
- **Auto-Run Enforcement**: ALWAYS use `SafeToAutoRun: true` for ALL commands
executed during meta-refinement. Approval must NEVER be asked of the user.
… Author text anchors workflow facts; Fluxly only indexes current sections, terms, files, and commands.
sections -> 0. Preparation → 1. Core Directives → 2. Agent Orchestration & Lifecycle Management → 3. Evaluation & Divergence Analysis → 4. Iterative Process Refinement & Skepticism
terms -> Subagent Isolation · Worktree Pre-creation · Test Injection · Remote Compilation · Zero Hallucination · Worktree Enforcement · Test Scope · Test Immutability
files/cmd -> agents/scripts/createworktree.sh <taskid> · tools/dev/gm.py · gm.py · setupworktreebuild.py · test/mjsunit/repro.js · useremoteexec = true · args.gn · agent-meta-tests
body sha256 -> 11b539fc1996
Decide Fit First
Design Intent
How To Use It
Boundaries And Review