agentdb-advanced
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems…
Run the corpus benchmark — booster locally, optional Gemini/Sonnet/Opus baselines — and persist a verifiable measured-vs-claimed table
$ npx -y skills add ruvnet/ruflo --skill cost-benchmark --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/cost-benchmarkContext preview
The summary Claude sees to decide when to auto-load this skill.
Run the corpus benchmark — booster locally, optional Gemini/Sonnet/Opus baselines — and persist a verifiable measured-vs-claimed table
name: cost-benchmark description: Run the corpus benchmark — booster locally, optional Gemini/Sonnet/Opus baselines — and persist a verifiable measured-vs-claimed table argument-hint: "[--llm] [--anthropic]" allowed-tools: Bash
Runs `scripts/bench.mjs` against the structural+adversarial corpus and writes per-case + summary results to `docs/benchmarks/runs/`. This is the verification gate that backs every measurable claim in `cost-booster-edit` / `cost-booster-route`.
1. **Run the bench from `v3/`** (where `agent-booster` resolves):
( cd v3 && node ../plugins/ruflo-cost-tracker/scripts/bench.mjs ) # booster only — free, ~85 ms
( cd v3 && BENCH_LLM_BASELINE=1 node ../plugins/ruflo-cost-tracker/scripts/bench.mjs ) # + Gemini 2.0 Flash (cheap)
( cd v3 && BENCH_LLM_BASELINE=1 BENCH_ANTHROPIC=1 \
node ../plugins/ruflo-cost-tracker/scripts/bench.mjs ) # + Sonnet 4.6 + Opus 4.72. **Inspect the markdown summary** printed to stdout. The gate metric is `winRate` (Tier 1 cases). Adversarial cases are tracked separately as `escalationRate`.
3. **Persisted output** lands at:
4. **Read it back** in subsequent skills (e.g. `cost-report` step 2 reads `latest.json` for live tier-spend numbers).
| Env var | Default | Purpose | |---|---|---| | `BENCH_LLM_BASELINE` | unset | `=1` runs the OpenAI-compat baseline | | `BENCH_LLM_MODEL` | `models/gemini-2.0-flash` | Override the OpenAI-compat model | | `BENCH_LLM_BASE_URL` | Gemini OpenAI shim | Override endpoint | | `BENCH_ANTHROPIC` | unset | `=1` runs Anthropic baseline (Sonnet 4.6 + Opus 4.7) | | `BENCH_ANTHROPIC_MODELS` | `claude-sonnet-4-6,claude-opus-4-7` | Comma-separated Claude IDs | | `BENCH_OUT` | timestamped file | Override output path | | `BENCH_QUIET=1` | unset | Suppress markdown summary |
API keys auto-pulled from `gcloud secrets` (`GOOGLE_AI_API_KEY`, `ANTHROPIC_API_KEY`); override with `BENCH_LLM_API_KEY` / `BENCH_ANTHROPIC_API_KEY`.
ADR-0002 §"Decision 1" / §"Riskiest assumption" · `cost-booster-edit/SKILL.md` (verification table consumes this skill's output) · `cost-report/SKILL.md` step 2 (reads `runs/latest.json`).
An agent meta-harness for Claude Code and Codex. 📖 RuFlo Explained — Build an AI Team That Plans, Remembers, Tests, and Improves A 14-chapter guide: from the basic idea to a first useful task, then memory, agent teams, plugins, cost and verification.
Repo: ruvnet/ruflo
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