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CB transcript-fixer

Corrects ASR/STT transcription errors — homophones, garbled terms, person-name errors, mixed Chinese/English — with dictionary rules plus Claude's built-in AI, no external API key required. Use to clean meeting notes, lecture transcripts, interviews or speech-recognition text, even when the user only says "fix this transcript". Not for structuring a clean transcript into minutes (use meeting-minutes-taker).

Not recommendedcritical or high security findings
daymade/claude-code-skills Agent Skills author: daymade MIT 80 files · 40 scripts body ≈ 4 701 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Corrects ASR/STT transcription errors — homophones, garbled terms, person-name errors, mixed Chinese/English — with dictionary rules plus Claude's built-in…

As a process B 67/100 · Nearly there — weak spots: result and completion, progress reporting

IntegrationAI and agentsPersonal productivitytype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
C
82/100
safety, quality, tests
Safety 60%
80
Quality 40%
85
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Failures and branches w 10
55
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.

For the author

Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 3

  • high Dangerous commands cmd-persistence references/team_collaboration.md:218
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    Register-ScheduledTask -Action $action -Trigger $trigger -TaskName "SyncTranscriptCorrections"
Medium and low: 2
  • low Dangerous commands cmd-cron-mention references/team_collaboration.md:209
    Mentions editing / listing crontab
    crontab -e
  • low Dangerous commands cmd-pipe-to-shell-known-host scripts/ensure_deps.py:36
    Pipe-to-shell installer from a well-known host (still executes remote code) (string literal in code, not executed)
    print("   Install uv first: curl -LsSf https://astral.sh/uv/install.sh | sh")
    code literal

Files scanned: 79. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • note edit-residue the text marks something as outdated (lines 31): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 67/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 55Failures and branches. 1 branches
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 4701 tokens
  • 100Steps. 24 steps
  • 100When it triggers. States when to use and when not to
  • 100Consistency. Name and required fields are in place
  • 100Running it twice. No mutating operations
  • 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
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • -311 of 14 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 410: enough signal without eating the budget
  • +4Structure: 16 headings
  • +3Step-by-step instructions: 24 items
  • +4Reference files are cited in the instructions (34 of 34)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.