aicodeking/deepseek-stack

ds-lessons

Find mistakes agents keep repeating in this repo and turn each into structure that blocks it, preferring types over lint over tests over docs, plus an end-of-session reflection.

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How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/aicodeking/deepseek-stack --skill ds-lessons

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

ds-lessons

An instruction an agent can skip is a wish. Make repeated mistakes fail loudly instead.

Steps

  1. Gather mistakes. Read the current session, recent commits, reverts, review comments, agent instruction files and workaround comments. Group them into classes. A class counts once it happened twice.
  2. For each class, pick the highest level that works:
  3. Structure: one owner per piece of state, one supported way per task, hidden internals, delete old patterns an agent would copy.
  4. Types: make the bad state impossible to write.
  5. Lint or CI check: the error message names the right file, type or function to use. If the bad pattern is already common, fail only on new additions.
  6. Test: checks behavior, not internals.
  7. Docs or agent rules: only for judgment calls that cannot be checked. Add a short example of the failure.
  8. Fix the most frequent classes now, one commit each.
  9. Prove each new check. Re-introduce a real past mistake, run the check, and show it fails. Then remove it and show it passes.
  10. Keep a table in the agent instruction file: rule, and what enforces it. If a rule already existed but nothing enforced it, treat it as a repeat and enforce it now.
  11. End-of-session reflection: list what went wrong, what took extra loops and what the user corrected. Route each item to a check, a skill edit or a rule. Drop one-off issues.

Stop when

  • Each chosen class has an enforcement that you showed failing on a real mistake.
  • Or you have handled the top three classes this session. Note the rest.

Rules

  • If the fix is structural, do not also add prose. The prose was the symptom.
  • Report each class with evidence, the level chosen, and why a higher level did not work.
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