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BB meeting-to-tasks

Полный цикл от записи встречи до планов разработки: локальная транскрибация с разбором экрана и скриншотами, извлечение списка задач, отдельный план разработки по SDD на каждую задачу, которой нужен код. Используй ВСЕГДА, когда пользователь дает путь к записи встречи или созвона и хочет получить задачи, план, поручения или разбор - даже если слово транскрибация не прозвучало. Триггеры: разбери встречу, что по итогам созвона, какие задачи со встречи, сделай план по записи, переговоры в задачи, meeting to tasks. НЕ для простой расшифровки речи без задач - там достаточно скила transcribe.

Desko77/claude-code-skills-1c Claude Code author: Desko77 MIT 1 file body ≈ 2 546 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Полный цикл от записи встречи до планов разработки: локальная транскрибация с разбором экрана и скриншотами, извлечение списка задач, отдельный план…

As a process B 70/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

AnalyzerSoftware developmentSales and CRMtype 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
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
B
70/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

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 · 0

✓ No critical or high findings

Files scanned: 1. 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 70/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 1 mutating operations with no state check
  • 60Failures and branches. 2 branches
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. No external tools needed
  • 100Steps. 8 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2546 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +3Description length 592: enough signal without eating the budget
  • +4Structure: 6 headings
  • +3Step-by-step instructions: 8 items
  • +4Has examples (3 code blocks)
  • +2Bilingual instructions (RU + EN)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.