# Bscost Theory Opt

> Build and validate theory-grounded optimization models for backside front-vs-back net cost (signal and clock), with strict metric contracts and stability gates against HPWL baselines. Use when users request principled model fitting, crossover reasoning, or promotion decisions from shadow mode to active optimization.

- **Type:** Skill
- **Install:** `agentstack add skill-mr-fang-vlsi-edagent-bscost-theory-opt`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [Mr-Fang-VLSI](https://agentstack.voostack.com/s/mr-fang-vlsi)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [Mr-Fang-VLSI](https://github.com/Mr-Fang-VLSI)
- **Source:** https://github.com/Mr-Fang-VLSI/EDAgent/tree/main/skills/bscost-theory-opt

## Install

```sh
agentstack add skill-mr-fang-vlsi-edagent-bscost-theory-opt
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# BS Cost Theory Opt

Use this skill when the task is to move from heuristic cost terms to a validated optimization model that can be promoted only after passing gates.

## Background Knowledge Links

This skill must stay grounded in:
1. KB workflow and policy context, especially:
- `docs/knowledge_base/80_BSCOST_THREE_SKILL_WORKFLOW_20260304.md`
- `docs/knowledge_base/84_REPLACE_COMPARISON_POLICY_20260304.md`
- relevant backside judgment KB notes when applicable.
2. Paper-derived evidence already summarized into local notes or paper-summary artifacts.
3. Experiment-experience artifacts from `eda-experiment-phenomenology-analyst` when related local runs already exposed reusable results, conclusions, or repeated failure patterns.
4. Scoped retrieval from `eda-context-accessor` when the task needs refreshed KB or paper context before fitting or promotion judgment.

If current empirical evidence contradicts the linked background knowledge:
- keep the contradiction explicit,
- block promotion if the theory basis is no longer defensible,
- request KB update or overturn follow-up when needed.

## Mandatory artifacts
1. `*.dataset.tsv` (dataset-level scorecard)
2. `*.per_fold.tsv` (fold-level evidence)
3. `*.summary.md` with final PASS/FAIL and open risks
4. include gate mode flag: `region_exact` vs `proxy_mode`

## Operational References

1. Load `references/background-knowledge-links.md` when identifying which KB docs, paper summaries, and theory assumptions are authoritative for the current modeling task.
2. Load `references/theory_formulation.md` when locking metric contract, sign convention, and physically meaningful feature blocks.
3. Load `references/optimization_and_gates.md` when running repeated validation, HPWL comparison, and promotion gating.
4. Load `references/internet_benchmark_notes.md` when extending beyond current datasets and benchmark provenance must be refreshed from primary sources.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [Mr-Fang-VLSI](https://github.com/Mr-Fang-VLSI)
- **Source:** [Mr-Fang-VLSI/EDAgent](https://github.com/Mr-Fang-VLSI/EDAgent)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-mr-fang-vlsi-edagent-bscost-theory-opt
- Seller: https://agentstack.voostack.com/s/mr-fang-vlsi
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.