SKILLEMALL.ai

BD meta-edit

Точечное редактирование объекта метаданных 1С. Используй когда нужно добавить, удалить или изменить реквизиты, табличные части, измерения, ресурсы или свойства существующего объекта конфигурации

Nikolay-Shirokov/cc-1c-skills Claude Code author: Nikolay-Shirokov MIT 10 files · 1 script body ≈ 1 189 tokens Open the sourcegithub.com analyzed 2 d ago

Точечное редактирование объекта метаданных 1С.

As a process D 42/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions

GeneratorSoftware developmentData and analyticsAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
85
Quality 40%
72
Run on models
none yet
Process rating
D
42/100
Unfinished process
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
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.

Obfuscation 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 files contain invisible characters, encoded commands or comments hidden from readers but visible to the model. What you read differs from what the agent sees.

For the author

Remove invisible characters (they usually sneak in through copy-paste) and encoded strings: no catalog will pass them. Instructions for the model must be readable by a human too.

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 Obfuscation uni-mixed-script-word scripts/meta-edit.ps1:2138
    Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (3 occurrences)
    if ($current -and $rp -match '^[А-Яа-яЁёA-Za-z_]\w*\s*:') {
  • medium Obfuscation uni-mixed-script-word scripts/meta-edit.py:2114
    Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (1 occurrence)
    if current and re.match(r"^[А-Яа-яЁёA-Za-z_]\w*\s*:", rp):
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Write Glob

Files scanned: 10. 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 42/100

  • 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
  • 30Running it twice. 4 mutating operations with no state check
  • 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 1189 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)
  • +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
  • +3Description length 194: enough signal without eating the budget
  • +4Structure: 8 headings
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (7 of 7)
  • +2Bilingual instructions (RU + EN)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.