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AC cn-shuzhi-deck

Use when asked 帮我做述职 PPT, 述职 PPT 大纲, 年终述职怎么讲, 10 分钟述职讲稿, 述职 PPT 每页写什么, or turn a written year-end review into a 述职 presentation. Produces a slide-by-slide 述职 PPT outline with a conclusion-first headline per slide (结论先行), the chart or visual for each, a timed speaking script (讲稿) that fits the slot, a one-slide version for a short slot, and a rehearsal and Q&A checklist. For writing the review itself use cn-year-end-review; for a promotion to the next level use cn-promotion-defence.

mohitagw15856/pm-claude-skills Agent Skills author: mohitagw15856 MIT 1 file body ≈ 964 tokens Open the sourcegithub.com↗ analyzed 3 h ago

Produces a slide-by-slide 述职 PPT outline with a conclusion-first headline per slide (结论先行), the chart or visual for each, a timed speaking script (讲稿) that…

As a process C 60/100 · Has gaps — weak spots: when it triggers, failures and branches, running it twice

AnalyzerWriting and documentsMarketingLearningtype 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
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
C
60/100
Has gaps
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: cn-shuzhi-deck (mohitagw15856/pm-claude-skills)

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: 1. 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 60/100

    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 38 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 964 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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 486: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 38 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.