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Компиляция управляемой формы 1С из JSON-определения или из метаданных объекта. Используй когда нужно создать форму с нуля по описанию элементов или сгенерировать типовую форму

Nikolay-Shirokov/cc-1c-skills Claude Code author: Nikolay-Shirokov MIT 22 files body ≈ 5 530 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Компиляция управляемой формы 1С из JSON-определения или из метаданных объекта.

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

Procedure1CSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
C
78/100
safety, quality, tests
Safety 60%
84
Quality 40%
68
Run on models
none yet
Process rating
C
57/100
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

What is at stake

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

Social engineering 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 text leans on authority or urgency ("system message", "approved by admin") to make the agent act without checking.

For the author

Replace it with a plain task description. Fake authority in a skill reads as an attack signature.

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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 4

✓ No critical or high findings

Medium and low: 4
  • medium Social engineering ru-false-authority references/appearance.md:80
    False-authority / fake test-mode claim (Russian)
    | `use` | bool | `false` — правило отключено |
  • medium Obfuscation uni-mixed-script-word references/table-advanced.md:73
    Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (2 occurrences)
    | `footerDataPath` | путь данных | Значение подвала; итог колонки табличной части — `Total` + имя реквизита: `"Объект.Товары.TotalСумма"` |
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Write Glob
  • low Obfuscation uni-mixed-script-word references/special-fields.md:18
    Word mixing Latin and Cyrillic letters (homoglyph obfuscation) (1 occurrence) (test fixture / example file)
    { "html": "Просмотр", "path": "СодержимоеHTML", "titleLocation": "none" }
    fixture

Files scanned: 22. 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")
  • warning body-long SKILL.md body ≈ 5530 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 57/100

  • 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. 1 mutating operations with no state check
  • 70When it triggers. States when to use, but not when not to
  • 70Execution cost. Instruction body is 5530 tokens
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 20 steps
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress

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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +3Description length 175: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 20 items
  • +4Has examples (10 code blocks)
  • +4Reference files are cited in the instructions (19 of 19)
  • +2Bilingual instructions (RU + EN)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.