AB cognitive-self-training
Daily cognitive training, dream review, dream-scene narration, and self-improvement loop for OpenClaw, Hermes, Codex, Claude Code, and other AI agents. Use when the user wants a bot to review today's learning, consolidate knowledge, run spaced repetition or active recall, connect concepts across domains, reason with tian-dao style deduction, generate a human-readable dream description of the reasoning process, configure random dream styles, learn from corrections/errors, update agent memory, schedule daily dream reviews, or generate a next-step improvement strategy.
As a process B 73/100 · Nearly there — weak spots: inputs and preconditions, 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: 11. 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 73/100
- 30Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 4 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 100Steps. 79 steps
- 100Failures and branches. 12 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2773 tokens
- 100Progress reporting. Reports progress
- low 13 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)
- +1No license
- +2Single-language instructions
- +3Description length 572: enough signal without eating the budget
- +4Structure: 14 headings
- +3Step-by-step instructions: 79 items
- +3Output format is stated explicitly
- +4Has examples (6 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.