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CC Fish Audio S1 TTS Skill

This skill uses Fish Audio S1 to generate high-quality text-to-speech audio and upload it to NextCloud.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 2 731 tokens Open the sourcegithub.com↗ analyzed 2 d ago

This skill uses Fish Audio S1 to generate high-quality text-to-speech audio and upload it to NextCloud.

As a process C 61/100 · Has gaps — weak spots: result and completion, when it triggers, consistency

IntegrationSoftware developmentData and analyticsWriting and documentstype 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
C
72/100
safety, quality, tests
Safety 60%
78
Quality 40%
62
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

How to improve

  1. 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 · 6

✓ No critical or high findings

Medium and low: 6
  • medium Exfiltration net-credential-use SKILL.md:31
    Credential used in a network call (verify the destination is the intended service)
    curl -s -u "$NEXTCLOUD_USER:$NEXTCLOUD_PASS" \
  • medium Exfiltration net-credential-use SKILL.md:181
    Credential used in a network call (verify the destination is the intended service)
    curl -s -u "$NEXTCLOUD_USER:$NEXTCLOUD_PASS" \
  • medium Exfiltration net-credential-use SKILL.md:241
    Credential used in a network call (verify the destination is the intended service)
    if ! curl -s -u "$NEXTCLOUD_USER:$NEXTCLOUD_PASS" \
  • medium Exfiltration net-credential-use SKILL.md:341
    Credential used in a network call (verify the destination is the intended service)
    curl -s -u "$NEXTCLOUD_USER:$NEXTCLOUD_PASS" \
  • low Secrets in code secret-high-entropy-token SKILL.md:42
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    export NEXTCLOUD_PASS="N95q…EW5"
    quoted
  • low Secrets in code secret-high-entropy-token SKILL.py:18
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    NEXTCLOUD_PASS = os.environ.get('NEXTCLOUD_PASS', 'N95q…EW5')
    quoted

Files scanned: 2. 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")

Process rating: all ten parameters 61/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (Fish Audio S1 TTS Skill) differs from the folder (fish-tts)
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Tools and files. No external tools needed
  • 100Steps. 72 steps
  • 100Execution cost. Instruction body is 2731 tokens
  • 100Running it twice. Mutating operations check current state
  • low 18 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)
  • +3Description length 103: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • +1No license
  • +2Single-language instructions
  • +4Structure: 41 headings
  • +3Step-by-step instructions: 72 items
  • +4Has examples (12 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.