SKILLEMALL.ai
GitHub ↗ RU Sign in

AB model-usage

Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model summary from codexbar cost JSON.

ClawHub Agent Skills author: Peter Steinberger v1.0.0 4 files body ≈ 373 tokens Open the sourceclawhub.ai↗ analyzed 36 h ago

Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown.

As a process B 68/100 · Nearly there — weak spots: failures and branches, progress reporting

IntegrationSoftware developmenttype 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
100/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
96
Active model run: 82% with skill · 55% without
Process rating
B
68/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
Tools and files w 18
60
the three weakest of ten parameters · all ten

The same skill appears in 4 more places: ClawHub, ClawHub, ClawHub, 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: 4. 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 68/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 60Tools and files. Uses tools (web) 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. 11 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 373 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +3Description length 291: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 11 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.

    Model run · 10 Sept 2026

    With the skill
    82%
    +27 pp vs baseline
    Without the skill (baseline)
    55%
    triggers: +100% / −100%

    Active All thresholds met · 7 cases · $0.046

    External checks

    ClawHub: clean
    This skill coherently summarizes local Codex or Claude model cost usage through CodexBar, with the local-log access and third-party CLI dependency disclosed.
    LLM: benign (high) · VirusTotal: benign · 10 Sept 2026