SKILLEMALL.ai

BC platonic-brainstorming

Optional design exploration for Platonic Coding Phases 1 and 2. Explores user intent, requirements, alternatives, and design before RFC formalization or implementation.

ClawHub Agent Skills author: caesar0301 v1.0.2 MIT-0 10 files · 2 scripts body ≈ 2 875 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
98
Quality 40%
65
Run on models
none yet
Process rating
C
57/100
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

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Dangerous commands cmd-background-process scripts/start-server.sh:118
    Starts a background / autostarted process (code comment)
    # Use nohup to survive shell exit; disown to remove from job table
    comment
  • low Dangerous commands cmd-background-process scripts/start-server.sh:121
    Starts a background / autostarted process
    disown "$SERVER_PID" 2>/dev/null

Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 57/100

  • 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
  • 40Result and completion. Does not say what the result is
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Failures and branches. 10 branches
  • 85Steps. 50 steps, 1 vague phrases
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2875 tokens
  • 100Running it twice. Mutating operations check current state
  • low The response is described with custom markup (4 tags): a typed call is more reliable

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
  • -5TODO / placeholder text left in the skill
  • -33 of 3 scripts are never mentioned in SKILL.md
  • +2Single-language instructions
  • +3Description length 168: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 50 items
  • +4Has examples (1 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.

External checks

ClawHub: clean
This skill is a coherent brainstorming workflow with an optional local browser companion, with the main risks being disclosed local file writes and a local web server that should not be exposed publicly.
LLM: benign (high) · VirusTotal: · 29 May 2026