BD youtube-podcaster
Extracts the original text of a Youtube video and converts it into a multi-voice AI podcast using Gemini for script generation, OpenAI for TTS, and a local Node.js API with FFmpeg. It also can show you the text of the Podcast in WebVTT format.
As a process D 47/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- 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 · 5
✓ No critical or high findings
Medium and low: 5
-
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:24High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha512-+sNRW…tGG+eFkqxAWRjASDW+ktS9…N9w==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:74High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha512-j+gKEx…ahh+s1F2HZ+wAce…RkU++ZWQr…uoQ==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:120High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…rvP+yUUf…4tH/iSSo…tEA==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:147High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…DmC+EJUz…RN4+0gEx…AvA==",
detector -
low Secrets in code
secret-high-entropy-tokenpackage-lock.json:153High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)"integrity": "sha5…ibj+tODHI5/+l06Au2Pcriv/Gmet…weg==",
detector
Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 47/100
- 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
- 30Running it twice. 3 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 100Steps. 9 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 534 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 243: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 9 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.
External checks
ClawHub: clean
This skill is a coherent local YouTube-to-podcast tool, but it handles API keys and sends transcript/script content to Gemini and OpenAI.
LLM: benign (high) · VirusTotal: · 29 May 2026