Qredence Documentation

meta-harness scaffolds a workspace, validates candidate harness.py files, runs an outer-loop search over prompt / retrieval / parsing / memory strategies, and exposes script-based query and report tools for inspecting search state.

Quick start

Run from the repo root:

# 0. (Optional) Clarify a fuzzy goal into structured config
uv run python plugins/meta-harness/scripts/clarify_task.py --workspace ./workspace

# 1. Initialize a workspace with baselines and starter config
uv run python plugins/meta-harness/scripts/init_workspace.py \
  --workspace ./workspace \
  --task_type qa \
  --num_baselines 3

# 2. Run the outer-loop search
uv run python plugins/meta-harness/scripts/meta_harness_scaffold.py \
  --workspace ./workspace \
  --iterations 30 \
  --candidates 2

# 3. Inspect the resulting search state
uv run python plugins/meta-harness/scripts/query_cli.py --workspace ./workspace summary
uv run python plugins/meta-harness/scripts/query_cli.py --workspace ./workspace top --metric accuracy -k 5

In Claude Code:

claude --plugin-dir ./plugins/meta-harness
/meta-harness:meta-harness

What gets created

init_workspace.py creates the stable workspace scaffold:

.gitignore
search_config.json
eval_results.json
proposer_skill.txt
workspace_manifest.json
history/candidates/candidate_*/harness.py baseline seeds
candidates/, logs/, traces/, and reports/ directories

meta_harness_scaffold.py creates the live search artifacts:

candidates/candidate_<iteration>_<variant>/harness.py
search_state.json
updated eval_results.json
per-iteration history, Pareto frontier, and best-by-metric state

Validation

uv run pytest plugins/meta-harness/tests

Last modified on May 19, 2026

Fleet-RLM

Fleet Prime Agent

Fleet Pi

GEPA Omni

Qredence Skills

Fleet Reasoner

Qredence Plugins

meta-harness plugin

Quick start

What gets created

Validation

​Quick start

​What gets created

​Validation

Quick start

What gets created

Validation