SKILLEMALL.ai

AC podcast-and-audiograms

The audio-to-social pipeline skill -- turn a podcast episode into short, branded, captioned clips and audiograms that drive people back to the full episode. Use when someone wants to repurpose a podcast, make podcast clips, create audiograms, or promote an episode on social. Uses the WAVES framework. Reads brand-profile + the episode first. Select clips by listener-retention data + timestamped transcript, not just an AI virality score, plus a strategic CTA back to the episode. The agent plans the clip strategy, briefs the clip/audiogram creation, plans the cadence, and writes hooks/CTAs; a clip or audiogram tool produces the clips; the creator finalizes; WoopSocial publishes on a schedule and does NOT record/edit/transcribe the podcast, generate clips, or host it. Captions are non-optional (85% sound-off). Never fabricates virality or clips someone's copyrighted podcast. Distinct from captions-and-clipping, content-recycling, and youtube-long-form.

ClawHub Agent Skills author: Social Media Skills v1.0.0 MIT-0 7 files body ≈ 1 616 tokens Open the sourceclawhub.ai analyzed 2 d ago

The audio-to-social pipeline skill -- turn a podcast episode into short, branded, captioned clips and audiograms that drive people back to the full episode.

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureYouTubeMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
C
56/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 56/100

    • 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. 9 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 100Tools and files. No external tools needed
    • 100Steps. 10 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1616 tokens
    • low No test case covers injection arriving through data

    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 962: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 10 items
    • +4Reference files are cited in the instructions (4 of 4)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

    External checks

    ClawHub: clean
    This skill is a coherent podcast repurposing guide that asks for relevant episode and brand materials and does not include hidden execution or credential-handling behavior.
    LLM: benign (high) · VirusTotal: · 23 Jul 2026