Foglamp vs GhostWriter by MyHandler: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Foglamp and GhostWriter by MyHandler — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Foglamp
Foglamp
Observability for AI agents: see the cost, latency, traces, and output quality of every LLM call with one SDK.
Key features
- Two-Line SDK Instrumentation: Wrap your model once and every generateText / streamText call is automatically instrumented.
- Per-Agent Spans and Spend: View per-agent spans, latency, and spend with the full call flow across orchestrator, researcher, writer, and critic.
- Evals: Score production traffic with code checks and LLM judges, including PII checks and pass-rate scoring.
- Distributed Traces: Waterfall every run with the exact prompt and response captured per span.
- Alerts: Set threshold rules on cost, latency, and error rate to catch problems early.
- Cost Intelligence: Know exactly what every call costs broken down by model, agent, and customer.
Best for
- Catching Cost Regressions: Detect a sudden 10x cost spike days after shipping before it drains the budget.
- Debugging Bad Output: Trace the exact prompt and response that produced a wrong or hallucinated answer.
- Quality Gating with Evals: Continuously score production traffic to verify agents stay accurate and PII-safe.
- Latency Monitoring: Alert when per-agent latency crosses a threshold so slow responses are caught fast.
- Per-Customer Spend Analysis: Break down LLM spend by customer and model to understand unit economics.
GhostWriter by MyHandler
MyHandler.ai
Windows writing assistant that reads the screen around your cursor on a hotkey double-tap and types a context-aware draft in your voice.
Key features
- Hotkey Double-Tap Drafting: No prompt or dictation is needed — a double-tap with the cursor in any text field triggers capture and drafting directly in place.
- Screen Context Capture: Reads the thread, form or partial sentence surrounding the cursor locally on the machine, using that on-screen context as the entire input.
- Writing Intent Classification: Determines whether the moment calls for a reply, a continuation, a filled-in answer or a fresh compose before writing a single word.
- Sender and Identity Mapping: Maps each message in a thread to its sender and works out which handle is the user's, so the draft answers the other party rather than the user's own words.
- Calendar Cross-Check: When a draft proposes a time, it is validated against the next two weeks of a connected calendar before the text appears.
- Selection Rewriting: Selecting existing text before the hotkey rewrites that selection instead of composing something new.
- Nothing Sent Automatically: The generated text appears at the cursor for the user to read, edit or delete; sending always remains a manual step.
- Local Vault with Zero-Retention Cloud: Capture runs against an encrypted vault on the user's own PC and the assembled context is processed by a zero-data-retention cloud model.
Best for
- Email Backlog: Clearing a queue of owed replies by drafting each one from the thread already on screen instead of retyping the same answer.
- Chat and Slack Replies: Answering a message in a team chat where the draft is grounded in who asked whom for what in the visible thread.
- Web Form Completion: Filling a blank answer box under a question on a web form or application without switching to a separate chat window.
- Sentence Continuation: Picking up a half-written paragraph exactly where it stops, without the assistant restating what was already typed.
- Meeting Scheduling Replies: Responding to a request for a time with a proposal that has already been checked against the user's calendar.
- Tone-Sensitive Rewrites: Selecting a blunt or rough draft and having it rewritten in the user's own voice before sending.