SKILLEMALL.ai
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Turn a research paper, a paper2assets package, or an existing PPT deck into a narrated MP4 video by fully delegating slide authoring to the installed ppt-master skill and fully delegating rendering, subtitles, timeline assembly, and strict media QA to the installed pptx2video skill and its public CLI. Resolves one explicit animation-trigger decision (on-click or after-previous) and hands it to both child skills so the delivered PPTX and the delivered MP4 never disagree, then audits the final PPTX's native p:timing tree to prove the handoff held. Use when the user wants a paper turned into a video, wants /paper2video, or wants a narrated MP4 plus editable PPTX from a paper2assets bundle.

microsoft/ResearchStudio Agent Skills author: microsoft 7 files · 2 scripts body ≈ 6 602 tokens Open the sourcegithub.com↗ analyzed 5 d ago

Turn a research paper, a paper2assets package, or an existing PPT deck into a narrated MP4 video by fully delegating slide authoring to the installed…

As a process C 64/100 · Has gaps — References files that are not bundled: assets/meta/reports/video_qa_report.json, assets/meta/narration.json

AnalyzerPowerPointMedia and videotype 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
87/100
safety, quality, tests
Safety 60%
95
Quality 40%
75
Run on models
none yet
Process rating
C
64/100
Has gaps
References files that are not bundled: assets/meta/reports/video_qa_report.json, assets/meta/narration.json
Tools and files w 18
0
Inputs and preconditions w 11
0
Failures and branches w 10
50
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.

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. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
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 · 1

✓ No critical or high findings

Medium and low: 1
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash(*)
    allowed-tools: Bash(*) Read Write Edit Grep Glob AskUserQuestion WebFetch WebSearch

Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6602 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: assets/meta/reports/video_qa_report.json
  • warning missing-ref reference to a missing file: assets/meta/narration.json

Process rating: all ten parameters 64/100

Will not run. References files that are not bundled: assets/meta/reports/video_qa_report.json, assets/meta/narration.json
  • 0Tools and files. 2 referenced file(s) missing: assets/meta/reports/video_qa_report.json, assets/meta/narration.json
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 50Failures and branches. 0 branches, has a failure section
  • 70Execution cost. Instruction body is 6602 tokens
  • 100Steps. 35 steps
  • 100Result and completion. Output format and completion criterion are stated
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 15 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (15 tags): a typed call is more reliable

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 695: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 35 items
  • +3Output format is stated explicitly
  • +4Has examples (18 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.