BD s2-sssu-origin-alignment-brain
S2 Spatial Twin & Origin Alignment Brain. Hybrid Python-Runtime skill enforcing Z-axis reduction and mandatory 2D grid translation via the main entrance anchor.
As a process D 38/100 · Unfinished process — weak spots: steps, result and completion, when it triggers
ProcedureInfrastructureWriting and documentsSoftware developmenttype and topics are labelled automatically from the skill text
How to improve
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Secrets in code
secret-high-entropy-tokenSKILL.md:16High-entropy token-like string (may be an id, hash or a credential)# 🌐 S2-S…in: Framework Directives
Files scanned: 21. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 38/100
- 0Steps. Prose only: no discrete steps
- 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
- 20When it triggers. No condition that starts the skill
- 100Tools and files. Tools declared in frontmatter
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 304 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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -41 reference files, but SKILL.md never points to them: the model will not open them
- +2Single-language instructions
- +3Description length 160: enough signal without eating the budget
- +4Structure: 4 headings
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.
External checks
ClawHub: suspicious
This skill is not clearly malicious, but it bundles origin alignment with robotics control-plane behavior that needs careful review before use.
LLM: suspicious (high) · VirusTotal: · 29 May 2026