Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add build-with-dhiraj/ai-workflow-framework-portability-kit/plugin install vercel-pluginWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/benchmark-sandbox)<a href="https://agentmods.dev/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/benchmark-sandbox"><img src="https://agentmods.dev/badge/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/benchmark-sandbox/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/benchmark-sandbox"><img src="https://agentmods.dev/badge/skills/build-with-dhiraj/ai-workflow-framework-portability-kit/benchmark-sandbox.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00051 | $0.05749 |
| Opus 5 | $0.00026 | $0.02874 |
| Sonnet 5 | $0.00010 | $0.01150 |
| Haiku 4.5 | $0.00005 | $0.00575 |
Grade B, and why
benchmark-sandbox scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
│ │ ├─ find ~/.claude/debug -type f (debug log count) Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
│ │ └─ curl localhost:3000 (port status) How it starts
The opening of the file, as written. The whole thing — 388 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark Sandbox — Remote Eval via Vercel Sandboxes
Run benchmark scenarios inside Vercel Sandboxes — ephemeral Firecracker microVMs with node24. Each sandbox gets a fresh Claude Code + Vercel CLI + agent-browser install, the local vercel-plugin uploaded, and runs a 3-phase eval pipeline:
- Phase 1 (BUILD): Claude Code builds the app with
--dangerously-skip-permissions --debug - Phase 2 (VERIFY): A follow-up Claude Code session uses
agent-browserto walk through user stories, fixing issues until all pass (20 min timeout) - Phase 3 (DEPLOY): A third Claude Code session links to vercel-labs, runs
vercel deploy, and fixes build errors (up to 3 retries). Deployed apps have deployment protection enabled by default.
Skills are tracked across all 3 phases — each phase may trigger additional skill injections as new files/patterns are created. After each phase, a haiku structured scoring step (claude -p --json-schema --model haiku) evaluates the results as structured JSON.
Proven Working Script
Use run-eval.ts — the proven eval runner:
# Run default scenarios with full 3-phase pipeline
bun run .claude/skills/benchmark-sandbox/run-eval.ts
# With dynamic scenarios from a JSON file (recommended — see "Dynamic Scenarios" below)
bun run .claude/skills/benchmark-sandbox/run-eval.ts --scenarios-file /tmp/my-scenarios.json
# Keep sandboxes alive overnight with public URLs
bun run .claude/skills/benchmark-sandbox/run-eval.ts --keep-alive --keep-hours 8
# Build-only (skip verification and deploy)
bun run .claude/skills/benchmark-sandbox/run-eval.ts --skip-verify --skip-deploy
# Run specific scenarios by slug
bun run .claude/skills/benchmark-sandbox/run-eval.ts --scenarios splitwise-clone,calendly-clone
CLI Flags
| Flag | Default | Description |
|---|---|---|
--concurrency N |
5 | Max parallel sandboxes (max 10) |
--timeout MS |
1800000 (30 min) | Per-phase timeout in ms |
--keep-alive |
off | Keep sandboxes running after eval |
--keep-hours N |
8 | Hours to keep alive (with --keep-alive) |
--skip-verify |
off | Skip the agent-browser verification phase |
--skip-deploy |
off | Skip the Vercel deploy phase |
--scenarios a,b,c |
all | Only run specific scenarios by slug |
--scenarios-file path |
— | Load scenarios from a JSON file instead of built-in defaults |
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 388 lines · 51 tokens per session scan B 2588bbda779e
benchmark-sandbox is a skill published in the GitHub repository build-with-dhiraj/ai-workflow-framework-portability-kit (4 stars, last pushed 28d ago), licensed MIT. It adds 51 tokens to every session and 5,749 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it B with 2 findings (reads agent configuration directories, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
semgrep-rule-variant-creator
Creates language variants of existing Semgrep rules. Use when porting a Semgrep rule to specified target languages. Takes an existing rule and target languages as input, produces independent rule+test directories for each language.
forward-derivation
Derive BDD scenarios and TDD test skeletons from approved SDD specifications. ATDD acceptance test tables are optional output for specialized needs. Use when: spec is approved, starting BDD/TDD implementation, generating test structures. Keywords: forward derivation, spec to test, BDD generation, TDD skeleton, test…
atdd-assistant
A guide to Acceptance Test-Driven Development, or ATDD, a process where a team agrees on user-story requirements and acceptance tests before coding. Acceptance tests check whether a feature meets the agreed business requirements.
testing-guide
A testing guide covering common testing levels, including unit, integration, system, and end-to-end testing. It also supports ISTQB and industry testing-pyramid approaches.
bdd-assistant
A guide to Behavior-Driven Development, or BDD, a way to describe software behavior with examples in plain language before building it. It uses Given-When-Then scenarios and Gherkin, a structured format for those examples.
methodology-system
Manage and guide developers through active development methodology workflows. Use when: TDD, BDD, SDD, ATDD, or custom methodology workflows are needed. Keywords: methodology, workflow, TDD, BDD, SDD, ATDD, phase, checkpoint, development process.