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BD Prezentit - AI Presentation Generator

GET /api/v1/me/credits Authorization: Bearer {PREZENTITAPIKEY} { "credits": 100, "pricing": { "outlinePerSlide": 5, "designPerSlide": 10, "estimatedCostPerSlide": 15 }, "ai": { "canGenerate": true,...

modbender/skill-library-mcp Agent Skills author: modbender MIT 1 file body ≈ 5 468 tokens Open the sourcegithub.com↗ analyzed 2 d ago

GET /api/v1/me/credits Authorization: Bearer {PREZENTITAPIKEY} { "credits": 100, "pricing": { "outlinePerSlide": 5, "designPerSlide": 10…

As a process D 36/100 · Unfinished process — weak spots: steps, result and completion, when it triggers

IntegrationPowerPointAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
80/100
safety, quality, tests
Safety 60%
100
Quality 40%
50
Run on models
none yet
Process rating
D
36/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5468 tokens (recommended < 5000); move details to references/

Process rating: all ten parameters 36/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (Prezentit - AI Presentation Generator) differs from the folder (prezentit)
  • 43Steps. 2 steps, 1 vague phrases
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 5468 tokens
  • 100Running it twice. No mutating operations

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)
  • +4Structure: 0 headings, hard to scan
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • -5Long text without headings
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 6 example trigger phrases
  • +3Description length 200: enough signal without eating the budget
  • +4Has examples (28 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 50.