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Experiments

AgentV eval files are the only runnable authoring artifact. Use top-level experiment: inside eval.yaml for runtime choices: targets, workers, timeout, sandbox/runtime knobs, budgets, thresholds, and repeat-run policy. AgentV does not have a separate experiment.yaml file, top-level run_group, or schema-significant experiments/ directory.

name: support-regression
experiment:
targets: [codex-gpt5, claude-sonnet]
workers: 2
timeout_seconds: 720
repeat:
count: 4
strategy: pass_at_k
cost_limit_usd: 2.00
workspace:
hooks:
before_all:
command: ["bash", "-lc", "bun install && bun run build"]
tests:
- id: refund-eligibility
input: Can this customer get a refund?
criteria: Applies the refund policy correctly

execution: is accepted only as a legacy top-level alias for existing eval files. Do not use both experiment: and execution: in the same eval.

Use directories for human organization, not schema behavior. A common layout is:

evals/
suites/
refunds.eval.yaml
cases/
refund-smoke.cases.yaml
experiments/
refunds-codex.eval.yaml

In that layout, evals/suites/refunds.eval.yaml is a reusable task suite, evals/cases/refund-smoke.cases.yaml is raw case data, and experiments/refunds-codex.eval.yaml is a wrapper eval. The wrapper still runs only because it is eval YAML:

experiments/refunds-codex.eval.yaml
experiment:
name: refunds-codex
target: codex-gpt5
workers: 2
tests:
- id: local-edge-case
input: Check a damaged final-sale refund.
imports:
suites:
- path: ../evals/suites/refunds.eval.yaml
tests:
- path: ../evals/cases/refund-smoke.cases.yaml

The experiments/ folder is optional and user-owned. AgentV does not scan it for special files or infer runtime behavior from the path; the same wrapper eval could live under evals/wrappers/, benchmarks/, or beside the suite it runs.

Use imports.suites for full child suites and imports.tests for raw test rows. Inline tests remain raw cases owned by the current file.

imports:
suites:
- path: evals/support/*.eval.yaml
select:
test_ids:
- refund-*
- missing-order-date
tags: regression
metadata:
priority: high
run:
threshold: 1.0
repeat:
count: 2
strategy: pass_all
tests:
- path: cases/*.cases.yaml
- path: cases/regression.jsonl
tests:
- cases/smoke/*.cases.yaml

imports.suites preserves the imported suite’s task contract: metadata, workspace, shared input, shared assertions, and tests. The parent eval still owns the single run bundle and runtime policy. Child suite experiment: blocks are ignored when imported; use parent experiment: for run policy and import run: for scoped threshold, repeat, timeout, or budget overrides.

A parent eval that imports any imports.suites entry must not define top-level workspace. Imported suites own task environment. If the parent should provide workspace context, import raw cases with imports.tests or shorthand paths instead of importing an eval suite.

imports.tests imports only raw test entries. It intentionally drops shared context from an imported eval suite, so parent suite fields apply to those raw cases.

Import select.test_ids filters imported test IDs with glob patterns. Import select.tags filters each imported case’s effective metadata.tags. Effective case tags are suite-first and deduped: suite.tags + suite.metadata.tags + test.metadata.tags. Top-level suite tags still remain suite identity metadata for discovery and reporting; selection reads the merged case metadata view. Import select.metadata filters case metadata by key/value, where selector values may be scalars or lists. Globbed include paths are resolved in deterministic path order, then test order.

String-valued tests and string entries inside tests[] are raw-case import shorthand. They are equivalent to imports.tests and may point at raw case files, directories, or globs. Importing another eval suite must use imports.suites.

Suite imports are resolved as a deterministic include graph. Circular imports.suites imports fail validation with the import chain; raw-case shorthand does not recursively load suite runtime blocks.

Imported suite rows keep their source suite metadata in index.jsonl. Use each row’s result_dir as the authoritative path to generated artifacts inside the run directory; do not infer layout from suite names.

Use scoped run: blocks for result interpretation and scheduling policies that vary by include group or test case. Precedence is:

test.run > import run > parent experiment
experiment:
target: agent
threshold: 0.8
repeat:
count: 3
strategy: pass_at_k
imports:
suites:
- path: ./evals/flaky-agentic/**/*.eval.yaml
select:
tags: [agentic]
run:
repeat:
count: 3
strategy: pass_at_k
- path: ./evals/regression/**/*.eval.yaml
select:
tags: [must-pass]
run:
threshold: 1.0
repeat:
count: 2
strategy: pass_all
tests:
- id: critical-case
input: "..."
criteria: Must pass exactly
run:
threshold: 1.0
repeat:
count: 1

Scoped run: supports threshold, repeat, timeout_seconds, and budget_usd. Candidate-changing fields such as target and targets stay parent-level under experiment:. Workspace mutation belongs in workspace.hooks, and runner-specific setup belongs in targets[].hooks.

experiment: configures evaluation policy. It does not own commands that prepare files, dependencies, repos, or target-specific runner state.

NeedPut it in
Install dependencies, build the repo, seed filesworkspace.hooks.before_all
Reset or apply per-case stateworkspace.hooks.before_each / workspace.hooks.after_each
Configure an agent runner or provider varianttargets[].hooks
Choose targets, repeats, pass policy, budget, thresholdexperiment
Bind an existing local workspace directory--workspace-path or .agentv/config.local.yaml
workspace:
hooks:
before_all:
command: ["bash", "-lc", "bun install && bun run build"]
targets:
- name: agent-with-skills
provider: codex
hooks:
before_each:
command: ["sh", "-c", "cp -R skills \"{{workspace_path}}/.codex/skills\""]
experiment:
target: agent-with-skills
repeat:
count: 3
strategy: pass_at_k

experiment.workspace is not an authored eval YAML field. Existing local workspace paths are machine-local bindings: pass --workspace-path for a one-off run or put execution.workspace_path in .agentv/config.local.yaml. Put repos, templates, hooks, Docker config, env checks, and isolation under top-level or case-level workspace.

repeat supports the same core strategies as repeated attempts:

experiment:
repeat:
count: 3
strategy: mean
cost_limit_usd: 1.50

Supported strategies:

StrategyBehavior
pass_at_kUses the best passing attempt; early-exits by default unless early_exit: false is set
pass_allUses the weakest attempt score, so every repeated attempt must meet the threshold
meanAggregates repeated attempt scores by mean
confidence_intervalUses the lower bound of a 95% confidence interval as the conservative score

AgentV also accepts runs and early_exit under experiment: as shorthand for repeat-run policy:

experiment:
runs: 4
early_exit: true

Do not set both repeat and runs in the same runtime block.

Eval runs write to the selected result bucket:

.agentv/results/<experiment>/<timestamp>/

CLI --experiment sets the bucket explicitly. Without that flag, AgentV uses experiment.name from the eval file, then default. The experiment remains the comparison and runtime-policy label for a run condition; folder names are only storage allocation and must not define result semantics.

Imported source suite metadata appears in index.jsonl rows and manifests. Use index.jsonl fields such as eval_path, test_id, target, and result_dir for identity and artifact discovery instead of reconstructing paths from suite names or wrapper layout.

For the complete result file contract, including why row metadata is semantic truth and directories are storage allocation, see Result Artifact Contract.