¿Puedo vibecodear LLM Pulse?
PARCIAL · un fin de semanaThe core loop is a realistic weekend build: run a fixed prompt set against a model API, detect brand and competitor mentions, collect citations, and chart the results. The gap appears when you need dependable runs across many models, long-term evidence, team access, exports, alerts, and the broader visibility and reputation workflow.
Build a local, single-user AI visibility tracker for one brand. Use Node.js 22, TypeScript, Express, better-sqlite3, server-rendered HTML, and vanilla JavaScript. Bind the app to localhost:4173 and provide one documented command for the first run. Keep MODEL_BASE_URL, MODEL_API_KEY, and MODEL_NAME in .env and ship a safe .env.example. Support one JSON chat endpoint configured entirely through those environment variables. Document the endpoint contract and isolate it behind one small adapter so it can be replaced later. Let the user configure one brand, aliases, three competitors, and up to 25 prompts. Run prompts manually and on a weekly local schedule with a clear API budget limit. Limit concurrency, retry transient failures, and keep failed prompts visible instead of dropping them. Store every prompt, raw answer, model name, timestamp, latency, and error in SQLite. Detect case-insensitive brand and competitor mentions using editable aliases. Extract and normalize URLs from answers, then preserve the source answer for every citation. Use one structured model pass to label brand sentiment as positive, neutral, negative, or absent. Calculate mention rate, citation rate, competitor share of voice, and net sentiment with documented formulas. Show current results, weekly trends, and a prompt-level evidence table on a compact dashboard. Make every aggregate metric link back to the raw answers used to calculate it. Export prompts, answers, mentions, citations, and weekly metrics as CSV files. Add backup and restore commands for the SQLite database. Do not add accounts, billing, teams, telemetry, web crawling, or an integration catalog. Do not claim parity with managed multi-model collection, reputation workflows, traffic analytics, or production monitoring. Write tests for alias matching, URL normalization, retry handling, and metric calculations. Include a README with setup, API cost controls, data location, backup steps, and limitations. Run the tests and production build before finishing, then list the exact commands used.
$ ábrelo en tu agente (prompt listo, tú das enter) o cópialo crudo
prompt copied. want to know what dies next week?
veredictos nuevos + votos de la semana. gratis. te sales en un clic.
Teams pay to keep large prompt sets running on schedule, preserve evidence over time, and analyze mentions, citations, sentiment, competitors, and traffic in one dependable workflow without maintaining the execution pipeline themselves.
xmanaged execution across the full model set
xlong-term historical comparisons and evidence
xreputation, source, traffic, and competitor workflows
xteam permissions, exports, alerts, and integrations
xproduction monitoring and support
¿No quieres construirlo? Esta gente ya lo hizo gratis.
ElmoTracks mentions, citations and competitors across the major engines; sentiment and referral traffic are still on the road map.open source↗sin votos, sin pago por aparecer · solo lo que es real
Precio de LLM Pulse
| plan | mensual | anual (por mes) | qué incluye |
|---|---|---|---|
| starter weekly | $56.52/workspace | $47.09/workspace | 1 project; 50 prompts; 50 AI responses/week/model; 10 competitors. |
| growth weekly | $114.19/workspace | $95.16/workspace | 2 projects; 150 prompts; 150 AI responses/week/model; 15 competitors. |
| scale weekly | $344.87/workspace | $287.39/workspace | 5 projects; 450 prompts; 450 AI responses/week/model; 20 competitors. |
| scale+ weekly | $690.89/workspace | $575.74/workspace | 10 projects; 1,200 prompts; 1,200 AI responses/week/model; 20 competitors. |
| scale++ weekly | $1382.93/workspace | $1152.44/workspace | 15 projects; 2,400 prompts; 2,400 AI responses/week/model; 25 competitors. |
| starter daily | $91.12/workspace | $75.93/workspace | 1 project; 50 prompts; 50 AI responses/day/model; 10 competitors. |
| growth daily | $171.86/workspace | $143.22/workspace | 2 projects; 150 prompts; 150 AI responses/day/model; 15 competitors. |
| scale daily | $517.88/workspace | $431.57/workspace | 5 projects; 450 prompts; 450 AI responses/day/model; 20 competitors. |
| scale+ daily | $1036.91/workspace | $864.09/workspace | 10 projects; 1,200 prompts; 1,200 AI responses/day/model; 20 competitors. |
| scale++ daily | $2190.31/workspace | $1825.26/workspace | 15 projects; 2,400 prompts; 2,400 AI responses/day/model; 25 competitors. |
| enterprise | a medida | — | Custom projects, prompt volume, refresh frequency, model coverage, data access, and support. |
plan gratisno free tier; 14-day card-required trial on weekly Starter, Growth, and Scale only; daily plans and Scale+/Scale++ start immediately
facturaciónmonthly + annual (annual is billed for 10 months, effectively 2 months free); VAT/tax may be added
costos ocultosAdditional AI models are sold as paid add-ons; public add-on rates are not disclosed.
verificado 2026-08-14 · fuente ↗
¿Puedo vibecodear LLM Pulse?
Parcial. El núcleo de LLM Pulse se arma en un fin de semana con el prompt de esta página, pero hay huecos reales: managed execution across the full model set, long-term historical comparisons and evidence. Lee la lista honesta arriba antes de comprometerte.
¿Cuánto cuesta LLM Pulse?
LLM Pulse cuesta unos $56.52/mes (Starter Weekly, revisado 2026-08-14), o sea $678.24 al año.
¿Qué pierdo si reemplazo LLM Pulse?
Con honestidad: managed execution across the full model set; long-term historical comparisons and evidence; reputation, source, traffic, and competitor workflows; team permissions, exports, alerts, and integrations; production monitoring and support. Si alguno de esos te sostiene el negocio, sigue pagando.
¿Hay una alternativa open source a LLM Pulse?
Sí: Elmo (Tracks mentions, citations and competitors across the major engines; sentiment and referral traffic are still on the road map.) El prompt es para cuando la quieres exactamente a tu modo.