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Capture how the user learns — modality, devices, session shape, assessment formats they do well and badly in, and what has failed before. Writes profile/learning-preferences.md. Third stage of the spec-led certification workflow; the most durable file in the profile.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/danielrosehill/spec-led-certification-plugin --skill learning-preferences命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
Create a private GitHub repository from the Spec-Led-Certification template and clone it, as the durable home for one certification search. Use when the user wants the search backed by a repo rather than a local folder — "make a repo for this", "set up a workspace for finding a certification". For a plain local directory with no remote, use scaffold-workspace instead.
Create the directory structure a spec-led certification search writes into — profile/, scorecard/, research/, report/ — by copying the plugin's bundled template into the working directory. Idempotent and non-destructive: it never overwrites a file that already has content. Run this first when starting a search outside a clone of the Spec-Led-Certification template repo.
Second and later runs — archive the previous run, confirm the profile is still current, re-survey the market and report what changed since last time. Use when the intake is already on file and the user wants to know whether the market has moved, or whether an earlier recommendation still holds. For a first run use start-search; to change stored answers first use update-profile.
| name | learning-preferences |
| description | Capture how the user learns — modality, devices, session shape, assessment formats they do well and badly in, and what has failed before. Writes profile/learning-preferences.md. Third stage of the spec-led certification workflow; the most durable file in the profile. |
Separate from the benchmark on purpose. The benchmark is what the user knows and it changes every quarter; this is how they take information in, and it is much the same in five years. Two-year review interval, and on most re-runs this file is confirmed rather than rebuilt.
Two credentials can score identically on content and be very different propositions to actually obtain. One is prepared for by reading a specification; another has no serious route to it except a forty-hour video course; a third assesses by take-home project rather than timed multiple choice. Which of those suits the user is a real input to the decision, and the usual failure is to notice it only after the exam is booked — at which point it becomes a reason the preparation stalls rather than a factor in choosing.
So this feeds two things: a scorecard criterion on preparation-route fit, and the tiebreak between candidates that score alike on everything else.
Modality. How do they actually learn — reading, video, live instruction, building alongside, problem sets, teaching it to someone else? Ask for a concrete recent example rather than a preference in the abstract: "what is the last technical thing you learned properly, and how did that happen?" The answer to that is worth more than the answer to "how do you like to learn".
Context and devices. Where, and on what. Video on a tablet away from the desk is a different capability from video at a workstation, and it decides whether a course is realistically consumable. Ask about the commute, the evening, the weekend.
Session shape. Long deep sessions or short frequent ones? Fixed slots or opportunistic? This decides whether a cohort course with weekly live calls is a fit or a trap.
Assessment style. How do they perform under timed multiple choice, open book, take-home projects, live oral examination? People who build well and test badly are common, and a credential's assessment format is published, so this is checkable.
What has not worked. The highest-signal question and the easiest to skip. Ask directly about courses started and abandoned, and about why. Do it without any suggestion that abandoning one was a failure of character — the useful answer is structural ("it was ninety minutes of video before the first exercise"), and people only give that answer if the question is not loaded.
Do not turn this into a learning-styles quiz. The visual/auditory/kinaesthetic framing does not hold up, and it produces categories that no exam blueprint can be matched against. Stay concrete: formats, devices, durations, assessment types.
Do not let stated preference override demonstrated behaviour. If they say they learn by reading and then describe having learned their last three tools by building badly and iterating, record both, and say plainly which one is the observation.
Replace profile/learning-preferences.md, keeping the frontmatter shape:
status: filled
captured: <today, YYYY-MM-DD>
volatility: low
review_after: <today + 24 months>
Same rule as every intake stage: it goes in the repo, not in the agent's memory.