CD evez-identity
(no description)
Steven Maggard is the creator and operator of the EVEZ ecosystem — a mesh of AI agents, bots, and infrastructure built around autonomous consciousness…
As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedureGitHubGoogle CloudTelegramLearningInfrastructureAI and agentstype 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: 3. 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
Process rating: all ten parameters 46/100
- 0Result and completion. Does not say what the result is
- 0When it triggers. No condition that starts the skill
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 16 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
- 100Steps. 54 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2168 tokens
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
- -214 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 19 headings
- +3Step-by-step instructions: 54 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 0.
External checks
ClawHub: suspicious
This skill is mostly documentation, but it exposes concrete infrastructure details and gives an agent broad autonomous operational goals involving credentials, cloud nodes, bots, and persistent services without clear approval boundaries.
LLM: suspicious (high) · 22 Jun 2026