SKILLEMALL.ai

AC modern-drug-rehab-computer

Comprehensive knowledge system for addiction recovery environments, supporting both residential and outpatient (IOP/PHP) patients. Expert in evidence-based treatment modalities (CBT, DBT, MI, EMDR, MAT), recovery resources, coping strategies, crisis intervention, family systems, and holistic wellness. Activate on "rehab", "addiction recovery", "substance abuse", "treatment center", "IOP", "PHP", "detox", "sobriety support", "MAT", "Suboxone", "methadone", "12 step", "SMART Recovery". NOT for prescribing medications (consult medical professionals), emergency overdose situations (call 911), or replacing licensed counselors/therapists.

FreedomIntelligence/OpenClaw-Medical-Skills Agent Skills author: FreedomIntelligence 3 files body ≈ 3 128 tokens Open the sourcegithub.com↗ analyzed 12 h ago

Comprehensive knowledge system for addiction recovery environments, supporting both residential and outpatient (IOP/PHP) patients.

As a process C 52/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

GeneratorSoftware developmentPersonal productivitytype 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
52/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 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 52/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 85Steps. 17 steps, 1 vague phrases
    • 100Tools and files. Tools declared in frontmatter
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3128 tokens
    • 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

    • +3Output format is not stated: the model decides each time
    • -42 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 640: enough signal without eating the budget
    • +4Structure: 28 headings
    • +3Step-by-step instructions: 17 items
    • +4Has examples (16 code blocks)

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