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BB pm-prd

Генерирует структурированный PRD (Product Requirements Document) с шаблонами под тип продукта (B2C / B2B / внутренний инструмент / платформа) — фон, цели, детальный дизайн фич, acceptance criteria в Given-When-Then, аналитика и 10-пунктовый чеклист качества. User-invoked only — do NOT auto-trigger. Triggers on /pm-prd, "сделай PRD", "напиши PRD", "продуктовые требования", "make a PRD", "write a PRD", "draft requirements doc".

serejaris/personal-corp-os Agent Skills author: serejaris MIT 3 files body ≈ 2 051 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Генерирует структурированный PRD (Product Requirements Document) с шаблонами под тип продукта (B2C / B2B / внутренний инструмент / платформа) — фон, цели…

As a process B 66/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

TemplateData 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
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
B
66/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Result and completion w 14
40
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 66/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (node) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 24 steps, 3 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2051 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • -5TODO / placeholder text left in the skill
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +3Description length 429: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 24 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.