SKILLEMALL.ai

BD cf-init

Создать пустую конфигурацию 1С (scaffold XML-исходников). Используй когда нужно начать новую конфигурацию с нуля

Nikolay-Shirokov/cc-1c-skills Claude Code author: Nikolay-Shirokov MIT 3 files · 1 script body ≈ 694 tokens Open the sourcegithub.com analyzed 2 d ago

Создать пустую конфигурацию 1С (scaffold XML-исходников).

As a process D 48/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions

Template1CAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
82/100
safety, quality, tests
Safety 60%
93
Quality 40%
65
Run on models
none yet
Process rating
D
48/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 3

✓ No critical or high findings

Medium and low: 3
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Glob
  • low Secrets in code secret-high-entropy-token scripts/cf-init.ps1:152
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    $f221…ion = $nl + "`t`t`t<Vers…ode>DontUse</Vers…ode>"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/cf-init.py:195
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    f221…ion = ("\r\n\t\t\t<Vers…ode>DontUse"
    quoted

Files scanned: 3. 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 48/100

  • 0Steps. Prose only: no discrete steps
  • 0Result and completion. Does not say what the result is
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 70When it triggers. States when to use, but not when not to
  • 100Tools and files. Tools declared in frontmatter
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 694 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 112: 120–800 characters recommended
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +4Structure: 4 headings
  • +4Has examples (3 code blocks)
  • +2Bilingual instructions (RU + EN)

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