AF outclaw-style
Learn the user's writing style per outreach channel (email, LinkedIn, Twitter/X, WhatsApp, Slack, SMS, Discord, Telegram — whatever is connected for this tenant). Runs the Prompt Learning Protocol from https://gist.github.com/milstan/3b12f938f344f4ae1f511dd19e56adce on ≥20 outbound samples per channel (falls back to what's available). Triggers on: 'learn my style', 'learn my voice', 'retrain style for <channel>', 'style report', 'how's my style score'. Auto-invoked (no user prompt) by outclaw-plan when a planned channel lacks a learned style for the current tenant.
As a process F 59/100 · Will not run — References files that are not bundled: scripts/message_classifier.py, scripts/style_evaluator.py
How to improve
- 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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: scripts/message_classifier.py - warning
missing-refreference to a missing file: scripts/style_evaluator.py
Process rating: all ten parameters 59/100
- 0Tools and files. 2 referenced file(s) missing: scripts/message_classifier.py, scripts/style_evaluator.py
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 1 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 100Steps. 22 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1750 tokens
- 100Progress reporting. Reports progress
- low The response is described with custom markup (24 tags): a typed call is more reliable
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)
- +1No license
- +2Single-language instructions
- +3Description length 571: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 22 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.