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genpark-billing-spend-anomaly-guard-skill

Real-time spend clarity anomaly detector identifying runaway agent token burn spikes with statistical Z-scores

Details

External ID
1387719847
Source
GITHUB
Company
—
Product
genpark-billing-spend-anomaly-guard-skill
Website domain
genpark.ai
Launched
Sept. 25, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.05976172175249808
Tags
agent-skills, ai-agent, anomaly-detection, mcp, mcp-server, metering-engine, model-context-protocol, pricing-matrix, python, usage-based-billing, zero-dependency
Fetched at
Sept. 27, 2026, 1:02 a.m.
Updated at
Sept. 27, 2026, 1:02 a.m.

Enrichment

Theme
revenue optimization and billing analytics
Vertical
Fintech
Function
Observability & eval
Audience
Developer
AI stance
AI feature
Project type
Hobby / open-source project
Normalized one-liner
token spend anomaly detector for ai agents
Manually corrected
False

Could you build this?

Yes It is a standard MCP skill that computes basic statistical metrics (Z-scores) on token usage time-series data to trigger anomaly alerts.

Competitors

Other products that read as similar to this one — 599 launches clear the similarity bar, closest 8 shown.

Attention rank: #483 of 600 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 329 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a observability & eval tool for Media & entertainment yet.