BB experiential-kolb-teaching
Runs a vault learning module as a Kolb experiential cycle (Concrete Experience -> Reflective Observation -> Abstract Conceptualization -> Active Experimentation) instead of a lecture. Opens with an experience, withholds the explanation, draws the claim out of the learner with Socratic question ladders scaled by Bloom level, routes the earned claim to an evergreen note, and closes with a retrieval check. Enforces desirable-difficulty discipline — never summarize for the learner, never name the concept before they have reconstructed its mechanism. Use when tutoring a genomics/ML module, designing a Kolb session, or deciding whether to explain or to ask. Trigger keywords — Kolb cycle, experiential teaching, tutor a module, desirable difficulty, never summarize, Socratic ladder, run a session.
Runs a vault learning module as a Kolb experiential cycle (Concrete Experience -> Reflective Observation -> Abstract Conceptualization -> Active…
As a process B 70/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice
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: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 70/100
- 0Result and completion. Does not say what the result is
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 6 mutating operations with no state check
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 8 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1989 tokens
- 100Progress reporting. Reports progress
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
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 800: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 8 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.