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Benchmark Models

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'Cross-model benchmark for gstack skills. Runs the same prompt through

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  • Added May 27, 2026
data-aigobashtestinggitapiperformance

Works with

  • cli
  • api

Security analysis

A100/100

Scanned May 27, 2026

npx -y skills add charlieviettq/awesome-agent-skill --skill benchmark-models --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: benchmark-models
description: 'Cross-model benchmark for gstack skills. Runs the same prompt through
  Claude, GPT (via Codex CLI), and Gemini side-by-side — compares latency, tokens,
  cost, and optionally quality via LLM judge. Answers "which model is actually best
  for this skill?" with data instead of vibes. Separate from /benchmark, which measures
  web page performance. Use when: "benchmark models", "compare models", "which model
  is best for X", "cross-model comparison", "model shootout". (gstack) Voice triggers
  (speech-to-text aliases): "compare models", "model shootout", "which model is best".'
---

## Skill routing

When the user's request matches an available skill, invoke it via the Skill tool. When in doubt, invoke the skill.

Key routing rules:
- Product ideas/brainstorming → invoke /office-hours
- Strategy/scope → invoke /plan-ceo-review
- Architecture → invoke /plan-eng-review
- Design system/plan review → invoke /design-consultation or /plan-design-review
- Full review pipeline → invoke /autoplan
- Bugs/errors → invoke /investigate
- QA/testing site behavior → invoke /qa or /qa-only
- Code review/diff check → invoke /review
- Visual polish → invoke /design-review
- Ship/deploy/PR → invoke /ship or /land-and-deploy
- Save progress → invoke /context-save
- Resume context → invoke /context-restore
```

Then commit the change: `git add CLAUDE.md && git commit -m "chore: add gstack skill routing rules to CLAUDE.md"`

If B: run `~/.claude/skills/gstack/bin/gstack-config set routing_declined true` and say they can re-enable with `gstack-config set routing_declined false`.

This only happens once per project. Skip if `HAS_ROUTING` is `yes` or `ROUTING_DECLINED` is `true`.

If `VENDORED_GSTACK` is `yes`, warn once via AskUserQuestion unless `~/.gstack/.vendoring-warned-$SLUG` exists:

> This project has gstack vendored in `.claude/skills/gstack/`. Vendoring is deprecated.
> Migrate to team mode?

Options:
- A) Yes, migrate to team mode now
- B) No, I'll handle it myself

If A:
1. Run `git rm -r .claude/skills/gstack/`
2. Run `echo '.claude/skills/gstack/' >> .gitignore`
3. Run `~/.claude/skills/gstack/bin/gstack-team-init required` (or `optional`)
4. Run `git add .claude/ .gitignore CLAUDE.md && git commit -m "chore: migrate gstack from vendored to team mode"`
5. Tell the user: "Done. Each developer now runs: `cd ~/.claude/skills/gstack && ./setup --team`"

If B: say "OK, you're on your own to keep the vendored copy up to date."

Always run (regardless of choice):
```bash
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)" 2>/dev/null || true
touch ~/.gstack/.vendoring-warned-${SLUG:-unknown}
```

If marker exists, skip.

If `SPAWNED_SESSION` is `"true"`, you are running inside a session spawned by an
AI orchestrator (e.g., OpenClaw). In spawned sessions:
- Do NOT use AskUserQuestion for interactive prompts. Auto-choose the recommended option.
- Do NOT run upgrade checks, telemetry prompts, routing injection, or lake intro.
- Focus on completing the task and reporting results via prose output.
- End with a completion report: what shipped, decisions made, anything uncertain.

## Step 0: Locate the binary

```bash
BIN="$HOME/.claude/skills/gstack/bin/gstack-model-benchmark"
[ -x "$BIN" ] || BIN=".claude/skills/gstack/bin/gstack-model-benchmark"
[ -x "$BIN" ] || { echo "ERROR: gstack-model-benchmark not found. Run ./setup in the gstack install dir." >&2; exit 1; }
echo "BIN: $BIN"
```

If not found, stop and tell the user to reinstall gstack.

---

## Step 1: Choose a prompt

Use AskUserQuestion with the preamble format:
- **Re-ground:** current project + branch.
- **Simplify:** "A cross-model benchmark runs the same prompt through 2-3 AI models and shows you how they compare on speed, cost, and output quality. What prompt should we use?"
- **RECOMMENDATION:** A because benchmarking against a real skill exposes tool-use differences, not just raw generation.
- **Options:**
  - A) Benchmark one of my gstack skills (we'll pick which skill next). Completeness: 10/10.
  - B) Use an inline prompt — type it on the next turn. Completeness: 8/10.
  - C) Point at a prompt file on disk — specify path on the next turn. Completeness: 8/10.

If A: list top-level gstack skills that have SKILL.md files (from `find . -maxdepth 2 -name SKILL.md -not -path './.*'`), ask the user to pick one via a second AskUserQuestion. Use the picked SKILL.md path as the prompt file.

If B: ask the user for the inline prompt. Use it verbatim via `--prompt "<text>"`.

If C: ask for the path. Verify it exists. Use as positional argument.

---

## Step 2: Choose providers

```bash
"$BIN" --prompt "unused, dry-run" --models claude,gpt,gemini --dry-run
```

Show the dry-run output. The "Adapter availability" section tells the user which providers will actually run (OK) vs skip (NOT READY — remediation hint included).

If ALL three show NOT READY: stop with a clear message — benchmark can't run without at least one authed provider. Suggest `claude login`, `codex login`, or `gemini login` / `export GOOGLE_API_KEY`.

If at least one is OK: AskUserQuestion:
- **Simplify:** "Which models should we include? The dry-run above showed which are authed. Unauthed ones will be skipped cleanly — they won't abort the batch."
- **RECOMMENDATION:** A (all authed providers) because running as many as possible gives the richest comparison.
- **Options:**
  - A) All authed providers. Completeness: 10/10.
  - B) Only Claude. Completeness: 6/10 (no cross-model signal — use /ship's review for solo claude benchmarks instead).
  - C) Pick two — specify on next turn. Completeness: 8/10.

---

## Step 3: Decide on judge

```bash
[ -n "$ANTHROPIC_API_KEY" ] || grep -q 'ANTHROPIC' "$HOME/.claude/.credentials.json" 2>/dev/null && echo "JUDGE_AVAILABLE" || echo "JUDGE_UNAVAILABLE"
```

If judge is available, AskUserQuestion:
- **Simplify:** "The quality judge scores each model's output on a 0-10 scale using Anthropic's Claude as a tiebreaker. Adds ~$0.05/run. Recommended if you care about output quality, not just latency and cost."
- **RECOMMENDATION:** A — the whole point is comparing quality, not just speed.
- **Options:**
  - A) Enable judge (adds ~$0.05). Completeness: 10/10.
  - B) Skip judge — speed/cost/tokens only. Completeness: 7/10.

If judge is NOT available, skip this question and omit the `--judge` flag.

---

## Step 4: Run the benchmark

Construct the command from Step 1, 2, 3 decisions:

```bash
"$BIN" <prompt-spec> --models <picked-models> [--judge] --output table
```

Where `<prompt-spec>` is either `--prompt "<text>"` (Step 1B), a file path (Step 1A or 1C), and `<picked-models>` is the comma-separated list from Step 2.

Stream the output as it arrives. This is slow — each provider runs the prompt fully. Expect 30s-5min depending on prompt complexity and whether `--judge` is on.

---

## Step 5: Interpret results

After the table prints, summarize for the user:
- **Fastest** — provider with lowest latency.
- **Cheapest** — provider with lowest cost.
- **Highest quality** (if `--judge` ran) — provider with highest score.
- **Best overall** — use judgment. If judge ran: quality-weighted. Otherwise: note the tradeoff the user needs to make.

If any provider hit an error (auth/timeout/rate_limit), call it out with the remediation path.

---

## Step 6: Offer to save results

AskUserQuestion:
- **Simplify:** "Save this benchmark as JSON so you can compare future runs against it?"
- **RECOMMENDATION:** A — skill performance drifts as providers update their models; a saved baseline catches quality regressions.
- **Options:**
  - A) Save to `~/.gstack/benchmarks/<date>-<skill-or-prompt-slug>.json`. Completeness: 10/10.
  - B) Just print, don't save. Completeness: 5/10 (loses trend data).

If A: re-run with `--output json` and tee to the dated file. Print the path so the user can diff future runs against it.

---

## Important Rules

- **Never run a real benchmark without Step 2's dry-run first.** Users need to see auth status before spending API calls.
- **Never hardcode model names.** Always pass providers from user's Step 2 choice — the binary handles the rest.
- **Never auto-include `--judge`.** It adds real cost; user must opt in.
- **If zero providers are authed, STOP.** Don't attempt the benchmark — it produces no useful output.
- **Cost is visible.** Every run shows per-provider cost in the table. Users should see it before the next run.

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