SKILLEMALL.ai
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CF office-pptx

Create, read, edit, and validate PowerPoint presentations (.pptx).

The skillemall take

The skill promises to create, read, and edit PowerPoint files: slide text, tables, images, charts. One instruction file, 1622 tokens, no scripts or linting errors. Quality score 81, safety 100, process 33. No critical findings.

It's built around LibreOffice and runs on most platforms. The low process score suggests minimal automation in testing or validation—just a straightforward instruction set. Works for basic presentation operations, but don't expect bulletproof handling of edge cases. Install it if you need a PPTX interface without complications.

deepseek-ai/deepseek-harness Agent Skills author: deepseek-ai MIT 1 file body ≈ 1 078 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Create, read, edit, and validate PowerPoint presentations (.pptx).

As a process F 28/100 · No process to follow — weak spots: steps, result and completion, when it triggers

AnalyzerPowerPointSoftware developmentData and analyticsWriting and documentstype 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
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
66
Run on models
none yet
Process rating
F
28/100
No process to follow
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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 28/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1078 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)
  • +3Description length 66: 120–800 characters recommended
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 3 headings
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.