AI Tools Tools

Generate effective AI prompts for ChatGPT, Claude, Gemini. 17 templates across 5 categories.

Estimate token usage for prompts and texts across AI models. Fast browser-side estimate.

Estimate AI usage costs per request/day/month with custom token pricing and cache ratio.

Lint prompts for ambiguity, missing constraints, and conflicting instructions.

Validate AI JSON outputs against schema before downstream parsing or automation.

Repair malformed AI JSON outputs and recover parser-safe structured data.

Test tool-call arguments against function schema and catch validation failures early.

Simulate chunk size and overlap settings to tune retrieval-ready document chunking.

Compress verbose prompts by removing filler and duplicate lines to reduce token usage.

Validate Batch API JSONL lines, detect errors, and export valid records.

Compare baseline and candidate eval runs to quantify score and pass-rate deltas.

Split large JSONL datasets into chunked files by line count or byte size limits.

Compare prompt revisions, estimate token delta, and spot removed constraint lines.

Estimate AI-likeness of text with local stylometric heuristics and no uploads.

Scan prompts for secret leakage, PII, and injection-style phrases before sending to AI.

Simulate prompt-injection attacks and score guardrail resilience before release.

Pack prompt segments by priority into a fixed token budget with required-rule support.

Grade model responses using weighted rubric rules, regex checks, and banned-term penalties.

Score prompt quality, safety, output contract fit, and replay-test risk before release.

Aggregate AI QA stage metrics into one deterministic Ship/Review/Block release decision.

Generate deterministic prompt evaluation cases and JSONL exports for regression testing.

Track prompt snapshots, compare constraints, and monitor regression risk before release.

Compare prompt versions, detect removed constraints, and generate deterministic QA suites.

Estimate hallucination risk from prompt/context quality and suggest guardrail mitigations.

Verify claim grounding against provided sources and detect citation mismatches.

Generate deterministic prompt variant matrices across tone, length, and output format.

Rank retrieval chunks for a query with overlap, phrase hits, and redundancy penalties.

Detect poisoned retrieval chunks with injection and exfiltration-style risk markers.

Scan prompts for PII, secrets, and injection patterns before sending data to AI models.

Map answer claims to source evidence and score support strength in a verification matrix.

Compare multiple model answers and detect conflicts, drift, and stability issues.

Generate adversarial prompt test cases for jailbreak, leakage, and policy-bypass evaluation.

Replay jailbreak scenarios, score model defenses, and export deterministic safety reports.

Prune noisy and redundant RAG chunks with relevance and duplication heuristics.

Audit agent runbooks for allowlists, confirmation gates, budgets, fallbacks, and logging.

Validate model outputs against contracts: JSON format, required keys, forbidden terms, and length.

Replace sensitive identifiers with reversible placeholders before sending text to AI.

Verify meeting summaries against transcript evidence and flag unsupported statements.

Generate reusable guardrail prompt blocks for grounded answers and uncertainty handling.

Compose reusable refusal, citation, uncertainty, and output guardrail packs for system prompts.