SKILLEMALL.ai

BC Statvs

Front door to STATVS (said status), the one append-only record of what happened across LifeOS and every app it runs: checks the record's health, says whether a system, app or site reports into it, writes rows, answers what happened, rebuilds and drills views, rewinds and replays past turns, and onboards a system through the five-step migration. USE WHEN statvs, status logging, status record, the record, is X logging to status, is my site reporting into status, full status logging, log this to status, write a status row, what happened, status tail, verify the record, status counters, drill, restore drill, rebuild a view, compare a view, rewind a turn, replay a miss, onboard X into status, migrate X to statvs, dual-write, register a stream. NOT FOR session status or why is this slow (the s shortcut), posting Vigil events or deciding what to text the principal (Vigil), complaints (Errata), memory recall (Cortex).

The skillemall take

Promises to be the front door to STATVS logging: check record health, answer what happened in the system, write log rows, rebuild views, rewind past states, migrate new systems. Contains 8 files, 1627 tokens, no linter errors. Quality score 79, process score 56; no critical findings but coverage gaps remain.

No model runs, no sandbox tests. Description cuts off mid-word, suggesting incomplete work. For a logging system that's a problem: unclear which commands work and how they interact with LifeOS. Install if you already know STATVS internals; otherwise you'll patch the instructions yourself.

danielmiessler/Personal_AI_Infrastructure Agent Skills author: danielmiessler 8 files body ≈ 1 627 tokens Open the sourcegithub.com↗ analyzed 28 h ago

Front door to STATVS (said status), the one append-only record of what happened across LifeOS and every app it runs: checks the record's health, says whether…

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

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
Run on models
none yet
Process rating
C
56/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    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: 8. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
    • note frontmatter-key unknown frontmatter key "evals"

    Process rating: all ten parameters 56/100

    • 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
    • 30Running it twice. 11 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 16 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1627 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • high The skill tells the model to perform an irreversible action with no human approval

    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
    • +3Description length 923: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.