DC s2-timeline-orchestrator
(no description)
Welcome to Phase 3 of the S2-Spatial-Primitive OS.
As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
ProcedureAI and agentsWriting and documentsMedia and videotype and topics are labelled automatically from the skill text
How to improve
- Add a description to the frontmatter: without it the skill never triggers.
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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
frontmatterSKILL.md: no YAML frontmatter block found - error
name-missingSKILL.md: frontmatter has no `name` - error
description-missingSKILL.md: no `description` — the skill can never trigger - note
edit-residuethe text marks something as outdated (lines 14): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 59/100
- 0Result and completion. Does not say what the result is
- 0When it triggers. No condition that starts the skill
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 30 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1460 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)
- +3Description length 0: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -227 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 10 headings
- +3Step-by-step instructions: 30 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.
External checks
ClawHub: suspicious
This smart-home timeline skill is not deceptive, but it should be reviewed because it saves unvalidated LLM-generated device schedules that may later drive real-world automation.
LLM: suspicious (high) · VirusTotal: · 14 Sept 2026