SKILLEMALL.ai

BC psychologist-analyst

Analyzes events through psychological lens using cognitive psychology, social psychology, developmental psychology, clinical psychology, and neuroscience. Provides insights on behavior, cognition, emotion, motivation, group dynamics, decision-making biases, mental health, and individual differences. Use when: Behavioral patterns, decision-making, group behavior, mental health, leadership, persuasion, trauma, development. Evaluates: Cognitive processes, emotional responses, motivations, biases, group dynamics, personality, mental states.

FreedomIntelligence/OpenClaw-Medical-Skills Agent Skills author: FreedomIntelligence 4 files body ≈ 14 871 tokens Open the sourcegithub.com↗ analyzed 15 h ago

Analyzes events through psychological lens using cognitive psychology, social psychology, developmental psychology, clinical psychology, and neuroscience.

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerResearchPersonal productivitytype and topics are labelled automatically from the skill text
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
C
56/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: RA-Skills

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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

  • warning body-long SKILL.md body ≈ 14871 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 56/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 12 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 40Execution cost. Instruction body is 14871 tokens: crowds the task out of the window
  • 55Failures and branches. 1 branches
  • 85Steps. 917 steps, 1 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • low 15 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

  • +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
  • +1No license
  • +2Single-language instructions
  • +3Description length 542: enough signal without eating the budget
  • +4Structure: 57 headings
  • +3Step-by-step instructions: 917 items
  • +4Has examples (0 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.