How do I install the Parameter Sweep Optimizer skill?

Run npx skillmds@latest add knuckles-team/parameter-sweep-optimizer in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Parameter Sweep Optimizer safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Parameter Sweep Optimizer?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Parameter Sweep Optimizer free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Parameter Sweep Optimizer?

Knuckles-Team (@knuckles-team) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Parameter Sweep Optimizer by knuckles-team

Name: Parameter Sweep Optimizer
Author: Knuckles-Team

File contents

Parameter Sweep Optimizer Workflow

CONCEPT:EE-011

Spawns 25 parallel parameter sweep configurations, extracts performance curves, plots response surfaces, and designates optimal param configs.

Steps

Step 1: Grid Search Sweeper

Agent: data-fetcher Tools: graph_query, sx_search

Spawns 25 parallel parameter configuration models. Expected: multi-parameter-backtest-records

Step 2: Metric Extractor [depends_on: grid-search-sweeper]

Agent: compute-engine Tools: graph_analyze

Extracts performance indicators and fit scores for each sweep node. Expected: extracted-response-metrics

Step 3: Surface Plotter [depends_on: metric-extractor]

Agent: risk-assessor Tools: graph_query, graph_analyze

Generates a 3D parameter response surface map to identify stable basins. Expected: volatility-response-surface-plot

Step 4: Config Selector [depends_on: surface-plotter]

Agent: report-generator Tools: graph_write, document_tools

Selects the parameters that minimize overfitting and registers them. Expected: finalized-parameter-configs

Step 5: KG Persistence [depends_on: config-selector]

Agent: report-generator Tools: graph_write

Persist workflow results as nodes and edges in the Knowledge Graph. Create appropriate typed nodes with metadata and link to existing domain entities.

Output

Parameter Sweep Optimizer results persisted in KG
Structured report (MD/PDF)
Audit trail with timestamps and agent attributions

Execution

Run this workflow as a dependency-ordered DAG. Steps with no unmet depends_on run in parallel; dependents run after their prerequisites complete.

Run first (in parallel): Step 1 — Grid Search Sweeper
After level 0: Step 2 — Metric Extractor
After level 1: Step 3 — Surface Plotter
After level 2: Step 4 — Config Selector
After level 3: Step 5 — KG Persistence

Execution: If graph-os is reachable, offload the whole DAG via graph_orchestrate action=execute_workflow (or the kg-delegate skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet depends_on in parallel, then their dependents.

---name: parameter-sweep-optimizerdescription: Spawns 25 parallel parameter sweep configurations, extracts performance curves, plots response surfaces, and designates optimal param configs.---# Parameter Sweep Optimizer Workflow**CONCEPT:EE-011**Spawns 25 parallel parameter sweep configurations, extracts performance curves, plots response surfaces, and designates optimal param configs.## Steps### Step 1: Grid Search Sweeper**Agent**: `data-fetcher`**Tools**: `graph_query, sx_search`Spawns 25 parallel parameter configuration models.Expected: `multi-parameter-backtest-records`### Step 2: Metric Extractor [depends_on: grid-search-sweeper]**Agent**: `compute-engine`**Tools**: `graph_analyze`Extracts performance indicators and fit scores for each sweep node.Expected: `extracted-response-metrics`### Step 3: Surface Plotter [depends_on: metric-extractor]**Agent**: `risk-assessor`**Tools**: `graph_query, graph_analyze`Generates a 3D parameter response surface map to identify stable basins.Expected: `volatility-response-surface-plot`### Step 4: Config Selector [depends_on: surface-plotter]**Agent**: `report-generator`**Tools**: `graph_write, document_tools`Selects the parameters that minimize overfitting and registers them.Expected: `finalized-parameter-configs`### Step 5: KG Persistence [depends_on: config-selector]**Agent**: `report-generator`**Tools**: `graph_write`Persist workflow results as nodes and edges in the Knowledge Graph.Create appropriate typed nodes with metadata and link to existing domain entities.## Output- Parameter Sweep Optimizer results persisted in KG- Structured report (MD/PDF)- Audit trail with timestamps and agent attributions## ExecutionRun this workflow as a dependency-ordered DAG. Steps with no unmet `depends_on` run in parallel; dependents run after their prerequisites complete.- **Run first (in parallel):** Step 1 — Grid Search Sweeper- **After level 0:** Step 2 — Metric Extractor- **After level 1:** Step 3 — Surface Plotter- **After level 2:** Step 4 — Config Selector- **After level 3:** Step 5 — KG Persistence**Execution:** If graph-os is reachable, offload the whole DAG via `graph_orchestrate action=execute_workflow` (or the `kg-delegate` skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet `depends_on` in parallel, then their dependents.

Frequently asked questions

Parameter Sweep Optimizer