SKILLEMALL.ai

AC openclaw-optimize

Audit and optimize OpenClaw token usage, cron job efficiency, and agent performance. Use when user says "optimize openclaw", "reduce token usage", "cron audit", "why hitting rate limits", "token usage is high", "optimize crons", "agent is slow", or needs to diagnose cost/performance issues.

ClawHub Agent Skills author: mrmps v1.0.0 MIT-0 2 files body ≈ 4 428 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

AnalyzerAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

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: 2. 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

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 70Execution cost. Instruction body is 4428 tokens
    • 100Tools and files. No external tools needed
    • 100Steps. 27 steps
    • 100Failures and branches. 10 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Progress reporting. Reports progress
    • low 10 top-level sections: this looks like several domains in one skill

    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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 7 example trigger phrases
    • +3Description length 291: enough signal without eating the budget
    • +4Structure: 39 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (22 code blocks)

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

    External checks

    ClawHub: clean
    This is an instruction-only OpenClaw optimization skill that asks the agent to inspect cron and session data and only apply changes after user approval.
    LLM: benign (high) · VirusTotal: · 29 May 2026