Replace LLM Pulse?

KINDA · weekend project

catalog price reference $57/mocategory 📈 seo & marketingreported replacement votes 0

The 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.

the prompt

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.

$ open in your agent (prompt prefilled, you press enter) or copy it raw

why people still pay

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.

what you lose

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

prior art to inspect before building

No mature prior art is listed for this record.

reported replacements · 0share on X ↗"LLM Pulse replacement research and build prompt"

questions

What does the LLM Pulse verdict mean?

The core job looks buildable, with meaningful gaps: managed execution across the full model set, long-term historical comparisons and evidence. Read the full tradeoff list before committing. This research record is not a hosted IVCIFY tool.

What price does this directory record show for LLM Pulse?

The directory records $57/month for Starter, checked 2026-08-03. Verify the source before making a purchase decision. This reference stays outside retail Stack Math unless current matched evidence supports the comparison.

What do I lose by replacing LLM Pulse?

Honestly: 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. If any of those are load-bearing for you, keep paying.

Is there an open-source alternative to LLM Pulse?

This record does not list mature open-source prior art. The build prompt remains available as a research starting point.