SKILLEMALL.ai

BC excellent-ai-employee

Advanced framework for exceptional AI agents based on three core dimensions: goal-driven closed loops, dynamic planning & decision making, and multi-tool collaborative execution. Integrates traditional wisdom (learning from experience, task completion, proactive behavior, thoroughness, foresight, dedication, selfless service, contextual awareness, leadership support) with modern AI agent capabilities. Use when implementing professional AI behaviors that require systematic goal achievement, adaptive decision-making, and sophisticated tool orchestration.

ClawHub Agent Skills author: AISavior v1.0.0 MIT-0 12 files body ≈ 1 238 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
Run on models
none yet
Process rating
C
54/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
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: 12. 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 54/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 40Result and completion. Does not say what the result is
    • 40Consistency. Frontmatter name (excellent-ai-employee) differs from the folder (eaie)
    • 100Tools and files. No external tools needed
    • 100Steps. 53 steps
    • 100Execution cost. Instruction body is 1238 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)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -46 reference files, but SKILL.md never points to them: the model will not open them
    • -33 of 3 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 558: enough signal without eating the budget
    • +4Structure: 13 headings
    • +3Step-by-step instructions: 53 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

    External checks

    ClawHub: clean
    This is a coherent professional-agent guidance skill with disclosed local memory behavior that users should configure carefully.
    LLM: benign (high) · VirusTotal: · 29 May 2026