caveman--caveman-evidence-review

Reviews Caveman Cloud cost, trace, and savings evidence through read-only queries.

Updated Dec 3, 2025
One-click install
npx skills add https://github.com/hhenrichsen/dots --skill caveman-caveman-evidence-review-hhenrichsen
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: caveman--caveman-evidence-review
Source: https://github.com/hhenrichsen/dots/tree/main/dot_skills/caveman/caveman-evidence-review
Command: npx skills add https://github.com/hhenrichsen/dots --skill caveman-caveman-evidence-review-hhenrichsen

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? It answers questions about where LLM spend goes and what Caveman Cloud found, using only current measured data instead of repository guesses, while keeping cost, savings, and headroom figures strictly separated. ## Core Features & Use Cases - Baseline reporting: Loads overview, costs, Cave Score, workflows, and verified savings reports scoped to the selected project. - Trace-based verification: Searches and inspects bounded trace cohorts to test explanations against control groups before claiming causes. - Read-only safety: Never starts, approves, cancels, or rolls back experiments, and never fetches prompt or completion payloads by default. - Use Case: When asked why LLM costs spiked last week, it pulls cost reports, compares suspect workflow traces against a control window, and reports findings with trace ids and exact time windows. ## Quick Start Ask the assistant to review what Caveman found about LLM spend and errors for the current project over the past seven days.

Frequently Asked Questions about caveman--caveman-evidence-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I review LLM cost evidence in Caveman Cloud?▼

Load context with caveman_context, then pull overview, costs, score, workflows, and verified_savings reports via caveman_report. Test the leading explanation with bounded trace searches and inspect representative traces before reporting findings.

How to investigate where LLM spend goes with traces?▼

Use caveman_trace_search with closed filters like workflow, model, or cost bounds over a bounded window, then compare a suspect cohort against a control cohort. Inspect a few high-signal traces with caveman_trace_get to confirm the pattern.

Can this skill start or roll back Caveman experiments?▼

No, it is strictly read-only and never starts, approves, cancels, or rolls back experiments. Proposed actions are reported as proposals only and deferred to the caveman-manage skill for lifecycle review.

Does the review fetch prompt or completion payloads?▼

No, payload retrieval stays off by default. Metadata, spans, timing, models, token counts, status, and optimizer attribution are sufficient unless the user explicitly requests payload review.

What happens if Caveman login or project selection is missing?▼

The review stops and asks the user to run caveman login or select a project. It never guesses an organization id or reads outside the project selected by Caveman context.