cost-trend
Read every docs/benchmarks/runs/*.json and surface drift in win rate, latency, escalation rate, and LLM-baseline cost over time
Profile →npx skills add ruvnet/ruflo --skill cost-trend --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Cost Trend The smoke gate is binary (`winRate ≥ 0.80` → pass/fail). The corpus benchmarks captured over time form a curve — and curves catch regressions the gate misses (win rate slowly creeping from 100% to 85% is "still passing" by smoke but a real degradation). This skill reads every persisted run in `docs/benchmarks/runs/*.json` and reports first→last deltas plus a per-run series, flagging regressions in win rate or latency. ## When to use - Before a release — check that the speedup hasn't drifted. - After expanding the corpus — verify older runs still hit the same win rate on the new corpus *they* reflected. - After upgrading `agent-booster` — surface latency / strategy changes. ## Steps 1. **Run the trend script** from the project root: ```bash node plugins/ruflo-cost-tracker/scripts/trend.mjs ``` Optional env: - `TREND_FORMAT=json` — emit JSON instead of markdown - `TREND_LIMIT=10` — consider only the most recent N runs 2. **Inspect the drift summary** — first vs last on win rate, avg latency, p99, escalation rate, speedup vs Gemini. 3. **Inspect the per-run series** — one row per run, including Sonnet 4.6 + Opus 4.7 baseline latencies if those were enabled (`BENCH_ANTHROP
- When to use
- Steps
- Cross-references
node plugins/ruflo-cost-tracker/scripts/trend.mjs
What does the cost-trend skill do?
Read every docs/benchmarks/runs/*.json and surface drift in win rate, latency, escalation rate, and LLM-baseline cost over time
How do I install it?
Run `npx skills add ruvnet/ruflo --skill cost-trend --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ruvnet/ruflo, a repository with 67,015 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.