AB retaincraft
Spaced repetition & FSRS-5 AI learning assistant with active recall, Feynman technique, interleaved practice, causal questioning. 间隔重复FSRS-5 AI学习助手，整合主动回忆、费曼学习法、交错练习、因果追问。 Evidence-based: distributed practice d=0.85, practice testing d=0.74, AI tutoring 0.63-1.3 SD. Multi-platform compatible: OpenClaw, WorkBuddy, Claude Code, Hermes Agent. Features: FSRS-5 spaced repetition (default), SM-2 fallback, forgetting curve, burnout detection, learning contract, weekly report. 169 tests, 24 CLI commands, 14 academic citations, zero external dependencies.
As a process B 72/100 · Nearly there — weak spots: when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 72/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
- 100Steps. 119 steps
- 100Result and completion. Output format and completion criterion are stated
- 100Failures and branches. 4 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3905 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 17 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)
- -259 emoji in the instructions: noise for the model
- +2Single-language instructions
- +3Description length 552: enough signal without eating the budget
- +4Structure: 39 headings
- +3Step-by-step instructions: 119 items
- +3Output format is stated explicitly
- +4Has examples (10 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.