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AC api-cost-tracker

Track, analyze, and optimize AI API costs across OpenAI, Anthropic, OpenRouter, Google, and other LLM providers. Parses billing data, usage logs, or API responses to produce cost breakdowns by model, feature, and time period. Identifies optimization opportunities (model downgrades, caching, prompt compression). Use when asked to analyze API costs, track AI spending, optimize LLM usage, create cost reports, find expensive API calls, compare model pricing, set budget alerts, or audit API usage. Triggers on "API costs", "how much am I spending", "optimize API usage", "cost breakdown", "LLM spending", "token usage", "billing analysis", "reduce API costs", "budget tracking".

ClawHub Agent Skills author: charlie-morrison v1.0.0 MIT-0 3 files body ≈ 794 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: failures and branches, consistency, progress reporting

IntegrationAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
C
64/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
Consistency w 8
40
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 64/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (api-cost-tracker) differs from the folder (ai-api-cost-tracker)
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 18 steps
    • 100Execution cost. Instruction body is 794 tokens
    • 100Running it twice. No mutating operations

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 9 example trigger phrases
    • +3Description length 678: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 18 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This is a local API cost-reporting skill that handles sensitive billing exports, but the included code does not access credentials or make network calls.
    LLM: benign (high) · VirusTotal: · 29 May 2026