SKILLEMALL.ai

BD wodeapp-ai

One API Key (WODEAPP_API_KEY) unlocks the full multi-modal stack on this account: text, vision, audio, and video — unified credits, no per-provider keys. Start with lightweight chat and generation; grow into page building, workflows, digital humans, and multi-engine video (e.g. Kling / Seedance / Runway / Sora). Platform + project MCP, REST bridge, 22 workflow step types with per-step models, instant publish, cloud-synced run history. Examples below are entry points, not a hard ceiling. Setup: MCP in openclaw.json / Cursor / Claude Desktop; see Quick Setup. Browser UI: https://wodeapp.ai/create.

ClawHub Agent Skills author: diankourenxia v1.0.18 MIT-0 3 files body ≈ 9 325 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentsMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
D
45/100
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: 3. 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")
  • warning body-long SKILL.md body ≈ 9325 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "always"
  • note frontmatter-key unknown frontmatter key "requires"
  • note frontmatter-key unknown frontmatter key "primaryCredential"
  • note frontmatter-key unknown frontmatter key "capabilities"
  • note frontmatter-key unknown frontmatter key "supported_models"
  • note frontmatter-key unknown frontmatter key "protocols"

Process rating: all ten parameters 45/100

  • 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
  • 30Running it twice. 56 mutating operations with no state check
  • 40Execution cost. Instruction body is 9325 tokens: crowds the task out of the window
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (web) that frontmatter does not declare
  • 100Steps. 51 steps
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 14 top-level sections: this looks like several domains in one skill

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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 602: enough signal without eating the budget
  • +4Structure: 55 headings
  • +3Step-by-step instructions: 51 items
  • +4Has examples (26 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: suspicious
This looks like a real WodeApp integration, but it needs review because it combines broad hosted-project control with unclear authentication and data-retention disclosures.
LLM: suspicious (high) · VirusTotal: · 29 May 2026