BD telegram-voice-messaging-recovery
Recover working OpenClaw Telegram voice messaging after upgrades or rebuilds. Restores the local faster-whisper transcription helper, keeps OpenClaw native inbound/outbound voice routing, and applies the proven config fix: `messages.tts.provider = microsoft`, `messages.tts.providers.microsoft.voice = en-IE-ConnorNeural`, `messages.tts.providers.microsoft.lang = en-IE`, plus explicit `plugins.entries.microsoft.enabled = true`. Use when voice notes transcribe correctly but outbound TTS replies fail, or when `microsoft: no provider registered` appears.
As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Recover working OpenClaw Telegram voice messaging after upgrades o… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 44/100
- 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. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (telegram-voice-messaging-recovery) differs from the folder (lessac-offline-voice-system)
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 22 steps
- 100Execution cost. Instruction body is 507 tokens
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
- -42 reference files, but SKILL.md never points to them: the model will not open them
- -32 of 6 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 555: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 22 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.