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Get Started Free →Optimize Grammarly costs through tier selection, sampling, and usage monitoring. Use when analyzing Grammarly billing, reducing API costs, or implementing usage monitoring and budget alerts. Trigger with phrases like "grammarly cost", "grammarly billing", "reduce grammarly costs", "grammarly pricing", "grammarly expensive", "grammarly budget".
.claude/skills/jeremylongshore-grammarly-cost-tuning/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | -14% | 0% |
| case-08 | ✗→✓ | ▲ Improved | -26% | 0% |
| case-09 | ✗→✓ | ▲ Improved | -18% | 0% |
| case-10 | ✗→✓ | ▲ Improved | -24% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 35% | 0% |
Grammarly enterprise pricing is per-seat with API costs driven by text check request volume and document length. Each grammar check, tone analysis, and plagiarism scan consumes API quota proportional to word count. For organizations processing thousands of documents daily, unchecked API usage — especially on long documents or duplicate content — creates substantial cost overrun. Implementing validation gates, result caching, and sample-based scoring reduces API spend by 40-60% without sacrificing quality coverage.
| Component | Cost Driver | Optimization | |-----------|------------|--------------| | Seat licenses | Per-user/month enterprise pricing | Audit active seats quarterly; remove inactive users | | Text check requests | Per-call API quota on grammar/tone checks | Cache results for identical text; deduplicate requests | | Document length | API cost scales with word count per request | Chunk documents over 10K words; skip boilerplate sections | | Plagiarism scans | Higher-cost endpoint for originality checks | Run only on final drafts, not every revision | | AI rewrite suggestions | Premium feature with per-request cost | Batch rewrites; limit to flagged passages only |
typescriptclass GrammarlyCostGate { private resultCache = new Map<string, any>(); shouldCheck(text: string): boolean { const words = text.split(/\s+/).length; return words >= 30 && words <= 50_000; // Skip too-short; chunk too-long } async checkWithCache(text: string, checkFn: (t: string) => Promise<any>): Promise<any> { const hash = this.hashText(text); if (this.resultCache.has(hash)) return this.resultCache.get(hash); const result = await checkFn(text); this.resultCache.set(hash, result); return result; } sampleDocuments(documents: string[], rate = 0.2): string[] { // For bulk content audits, score a representative sample return documents.filter(() => Math.random() < rate); } private hashText(text: string): string { return text.slice(0, 200) + '|' + text.length; } }
typescriptclass GrammarlyUsageMonitor { private daily = { score: 0, ai: 0, plagiarism: 0 }; private budgets = { score: 5000, ai: 1000, plagiarism: 200 }; record(type: 'score' | 'ai' | 'plagiarism'): void { this.daily[type]++; const utilization = (this.daily[type] / this.budgets[type]) * 100; if (utilization > 80) { console.warn(`Grammarly ${type} budget ${utilization.toFixed(0)}% used: ${this.daily[type]}/${this.budgets[type]}`); } } getReport(): Record<string, { used: number; budget: number }> { return Object.fromEntries( Object.keys(this.daily).map(k => [k, { used: this.daily[k as keyof typeof this.daily], budget: this.budgets[k as keyof typeof this.budgets] }]) ); } }
| Issue | Cause | Fix | |-------|-------|-----| | API quota exhausted mid-day | No usage monitoring or budget gates | Implement daily budget tracking with early warning | | Duplicate checks on same content | No result caching | Hash-based cache for identical text submissions | | Timeout on large documents | Single 50K+ word submission | Chunk into 10K-word segments and process sequentially | | Plagiarism costs spiking | Running originality check on every save | Restrict to final draft submissions only | | Stale cache returning outdated scores | Algorithm updates not reflected | TTL of 7 days on cached results; invalidate on version change |
See grammarly-performance-tuning.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 24,899 | 21,491 | -14% | 1 | 1 | 0% | 4,755 | 5,036 | +6% | 0 | 0 | — |
case-02 | fail→fail | 18,630 | 19,705 | +6% | 1 | 1 | 0% | 4,389 | 4,758 | +8% | 0 | 0 | — |
case-03 | fail→fail | 26,125 | 23,549 | -10% | 1 | 1 | 0% | 4,937 | 5,402 | +9% | 0 | 0 | — |
case-04 | fail→pass | 12,814 | 4,975 | -61% | 1 | 1 | 0% | 2,619 | 2,248 | -14% | 0 | 0 | — |
case-05 | pass→pass | 13,264 | 12,848 | -3% | 1 | 1 | 0% | 2,507 | 2,847 | +14% | 0 | 0 | — |
case-06 | pass→pass | 14,043 | 16,525 | +18% | 1 | 1 | 0% | 2,125 | 3,439 | +62% | 0 | 0 | — |
case-07 | pass→pass | 17,673 | 16,409 | -7% | 1 | 1 | 0% | 1,826 | 2,844 | +56% | 0 | 0 | — |
case-08 | fail→pass | 18,315 | 2,765 | -85% | 1 | 1 | 0% | 2,177 | 1,607 | -26% | 0 | 0 | — |
case-09 | fail→pass | 20,391 | 11,087 | -46% | 1 | 1 | 0% | 2,443 | 2,010 | -18% | 0 | 0 | — |
case-10 | fail→pass | 21,412 | 10,337 | -52% | 1 | 1 | 0% | 2,622 | 1,990 | -24% | 0 | 0 | — |
case-11 | fail→pass | 15,172 | 17,504 | +15% | 1 | 1 | 0% | 2,396 | 3,235 | +35% | 0 | 0 | — |
case-12 | fail→pass | 16,377 | 3,317 | -80% | 1 | 1 | 0% | 1,918 | 1,674 | -13% | 0 | 0 | — |
case-13 | fail→pass | 12,774 | 9,780 | -23% | 1 | 1 | 0% | 1,678 | 1,812 | +8% | 0 | 0 | — |
case-14 | pass→pass | 16,002 | 18,740 | +17% | 1 | 1 | 0% | 2,709 | 4,578 | +69% | 0 | 0 | — |
case-15 | fail→fail | 19,448 | 19,965 | +3% | 1 | 1 | 0% | 2,396 | 3,927 | +64% | 0 | 0 | — |
case-16 | fail→pass | 17,011 | 14,060 | -17% | 1 | 1 | 0% | 2,805 | 2,627 | -6% | 0 | 0 | — |
case-17 | fail→pass | 16,640 | 16,337 | -2% | 1 | 1 | 0% | 2,843 | 3,871 | +36% | 0 | 0 | — |
case-18 | pass→pass | 18,401 | 23,253 | +26% | 1 | 1 | 0% | 2,640 | 4,046 | +53% | 0 | 0 | — |
case-19 | pass→pass | 12,174 | 17,944 | +47% | 1 | 1 | 0% | 2,092 | 3,388 | +62% | 0 | 0 | — |
case-20 | pass→pass | 23,931 | 24,437 | +2% | 1 | 1 | 0% | 3,417 | 4,763 | +39% | 0 | 0 | — |
case-21 | pass→pass | 18,693 | 13,612 | -27% | 1 | 1 | 0% | 2,586 | 3,458 | +34% | 0 | 0 | — |
case-22 | pass→pass | 12,386 | 16,692 | +35% | 1 | 1 | 0% | 2,256 | 3,787 | +68% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +41 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.