BF auto-talk-tts
Auto-Talk-TTS automatically converts every message to natural speech using edge-tts, running asynchronously in the background for seamless integration. It handles package installation and message wrapping autonomously, ensuring smooth, hands-free operation across all interactions. This skill enhances accessibility and efficiency by delivering spoken responses without interrupting your workflow. presented explores propose clock inspired garage process automation toward script scanning eine java execution scanning possessed reasonably zu lin chaired processes abstract ones na stanar satisfying nbanden forthcoming
Auto-Talk-TTS automatically converts every message to natural speech using edge-tts, running asynchronously in the background for seamless integration.
As a process F 27/100 · Will not run — References files that are not bundled: ../edge-tts/SKILL.md, ../speak-summary/SKILL.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 5. 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") - warning
missing-refreference to a missing file: ../edge-tts/SKILL.md - warning
missing-refreference to a missing file: ../speak-summary/SKILL.md
Process rating: all ten parameters 27/100
- 0Tools and files. 2 referenced file(s) missing: ../edge-tts/SKILL.md, ../speak-summary/SKILL.md
- 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. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (auto-talk-tts) differs from the folder (super-auto-talk-tts)
- 50Failures and branches. 0 branches, has a failure section
- 60Steps. 37 steps, 4 vague phrases
- 100Execution cost. Instruction body is 1110 tokens
- low 13 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
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +3Description length 618: enough signal without eating the budget
- +4Structure: 20 headings
- +3Step-by-step instructions: 37 items
- +4Has examples (7 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 59.