agentsclimarketplace

Clari cost tuning

Skill ComeOnOliver/skillshub/skills/jeremylongshore/claude-code-plugins-plus-skills/clari-cost-tuning

🧠 The right skill, one API call. AI agent skills registry with token-efficient skill resolution. 5,000+ skills from 500+ top repos.

Install
npx -y skills add ComeOnOliver/skillshub --skill clari-cost-tuning

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

Optimize Clari API usage and integration costs. Use when reducing API call volume, optimizing export frequency, or evaluating Clari license utilization. Trigger with phrases like "clari cost", "clari api usage", "reduce clari calls", "clari optimization".

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

2.2 KB, 415 tokens by cl100k_base, as published. Nobody here has run it

Clari Cost Tuning

Overview

Minimize Clari API overhead: reduce export frequency, cache aggressively, export only needed data types, and monitor usage.

Instructions

Export Only What You Need

# Full export (6 data types) -- more API load
full_types = ["forecast", "quota", "forecast_updated",
              "adjustment", "crm_total", "crm_closed"]

# Minimal export (2 data types) -- faster and lighter
minimal_types = ["forecast", "crm_closed"]

# Use minimal for dashboards, full for audit/compliance

Optimize Export Frequency

Use CaseRecommended Frequency
Executive dashboardDaily
Forecast accuracy trackingWeekly
Compliance auditQuarterly
Ad-hoc analysisOn demand

Cache to Avoid Redundant Exports

# Cache recent exports (see clari-performance-tuning)
cache = ExportCache(ttl_hours=8)

def smart_export(client, forecast_name, period):
    cached = cache.get(forecast_name, period)
    if cached:
        print(f"Cache hit for {period}")
        return cached

    data = client.export_and_download(forecast_name, period)
    entries = data.get("entries", [])
    cache.set(forecast_name, period, entries)
    return entries

Usage Tracking

class ClariUsageTracker:
    def __init__(self):
        self.api_calls = 0
        self.exports = 0

    def track_call(self):
        self.api_calls += 1

    def track_export(self):
        self.exports += 1

    def report(self) -> dict:
        return {
            "api_calls": self.api_calls,
            "exports": self.exports,
        }

Resources

Next Steps

For architecture patterns, see clari-reference-architecture.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.