managing-openai-api

name	managing-openai-api
description	Use when working with Openai Api — openAI API platform management covering models, usage, fine-tuning jobs, files, assistants, and billing. Use when monitoring API usage and costs, analyzing model performance, reviewing fine-tuning status, managing assistants and files, or troubleshooting OpenAI API issues.
connection_type	openai
preload	false

OpenAI API Management Skill

Manage and analyze OpenAI API resources including models, usage, fine-tuning, and billing.

API Conventions

Authentication

All API calls use Bearer API key, injected automatically.

Base URL

https://api.openai.com/v1

Core Helper Function

#!/bin/bash

openai_api() {
    local method="$1"
    local endpoint="$2"
    local data="${3:-}"

    if [ -n "$data" ]; then
        curl -s -X "$method" \
            -H "Authorization: Bearer $OPENAI_API_KEY" \
            -H "Content-Type: application/json" \
            "https://api.openai.com/v1${endpoint}" \
            -d "$data"
    else
        curl -s -X "$method" \
            -H "Authorization: Bearer $OPENAI_API_KEY" \
            "https://api.openai.com/v1${endpoint}"
    fi
}

Output Rules

• Target ≤50 lines per script output
• Use jq to extract only needed fields
• Never dump full API responses

Phase 1: Discovery

#!/bin/bash
echo "=== Available Models ==="
openai_api GET "/models" \
    | jq -r '.data[] | "\(.id)\t\(.owned_by)\t\(.created | strftime("%Y-%m-%d"))"' \
    | sort | head -25

echo ""
echo "=== Fine-Tuning Jobs ==="
openai_api GET "/fine_tuning/jobs?limit=10" \
    | jq -r '.data[] | "\(.id[0:20])\t\(.model)\t\(.status)\t\(.created_at | strftime("%Y-%m-%d"))"' \
    | column -t | head -10

echo ""
echo "=== Uploaded Files ==="
openai_api GET "/files" \
    | jq -r '.data[] | "\(.id[0:20])\t\(.filename[0:30])\t\(.purpose)\t\(.bytes) bytes"' \
    | column -t | head -15

echo ""
echo "=== Assistants ==="
openai_api GET "/assistants?limit=20" \
    | jq -r '.data[] | "\(.id[0:20])\t\(.name // "unnamed")\t\(.model)\t\(.created_at | strftime("%Y-%m-%d"))"' \
    | column -t | head -15

Phase 2: Analysis

Usage & Billing

#!/bin/bash
echo "=== Usage Summary (current billing period) ==="
START=$(date -d 'first day of this month' +%Y-%m-%d)
END=$(date +%Y-%m-%d)
openai_api GET "/organization/usage?start_date=${START}&end_date=${END}" \
    | jq '{total_tokens: .total_usage, daily_costs: [.daily_costs[-7:][] | {date: .timestamp | strftime("%Y-%m-%d"), cost_usd: (.line_items | map(.cost) | add / 100)}]}'

echo ""
echo "=== Cost by Model (current month) ==="
openai_api GET "/organization/usage?start_date=${START}&end_date=${END}" \
    | jq -r '.daily_costs[] | .line_items[] | "\(.name)\t$\(.cost / 100)"' \
    | awk -F'\t' '{costs[$1] += $2} END {for (m in costs) printf "%s\t$%.2f\n", m, costs[m]}' \
    | sort -t$'\t' -k2 -rn | head -15

Fine-Tuning Health

#!/bin/bash
echo "=== Fine-Tuning Job Status ==="
openai_api GET "/fine_tuning/jobs?limit=20" \
    | jq -r '.data[] | .status' | sort | uniq -c | sort -rn

echo ""
echo "=== Active/Recent Fine-Tuning ==="
openai_api GET "/fine_tuning/jobs?limit=10" \
    | jq -r '.data[] | "\(.id[0:20])\t\(.model)\t\(.status)\t\(.trained_tokens // 0) tokens\t\(.finished_at // "in progress" | if type == "number" then strftime("%Y-%m-%d") else . end)"' \
    | column -t

echo ""
echo "=== Fine-Tuned Models ==="
openai_api GET "/models" \
    | jq -r '.data[] | select(.owned_by != "openai" and .owned_by != "system") | "\(.id)\t\(.owned_by)\t\(.created | strftime("%Y-%m-%d"))"' \
    | head -10

Output Format

=== OpenAI Account ===
Models Available: <n>  Custom Fine-Tuned: <n>

--- Usage (current month) ---
Total Cost: $<amount>
Top Models: <model>: $<cost>

--- Fine-Tuning ---
Active: <n>  Completed: <n>  Failed: <n>

--- Resources ---
Files: <n>  Assistants: <n>

Anti-Hallucination Rules

1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations

Shortcut	Counter	Why
"I'll skip discovery and check known resources"	Always run Phase 1 discovery first	Resource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"	Follow the full discovery → analysis flow	Quick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"	Audit configuration explicitly	Defaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"	Always check relevant metrics when available	API/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"	Try the command and report the actual error	Assumed permission failures prevent useful investigation; actual errors are informative

Common Pitfalls

• Rate limits: Vary by model and tier (TPM and RPM limits); check response headers
• Usage API: May require organization-level API key for billing endpoints
• Timestamps: Unix epoch seconds in responses
• Fine-tuning models: Only specific base models support fine-tuning
• Pagination: Use limit and after cursor; check has_more in response