dev-guide-skill-stewardship

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Nested lingtai-dev-guide reference for turning one-off experience into durable skills: when to write a skill vs leave it as notes, the router-vs-nested- reference pattern, distilling experience (归一) and session journals into triggered/executable SKILL.md files, de-privatizing and parameterizing local paths and human-specific details, a lightweight pre-publish benchmark/checklist, grooming shared-library candidates, and PR-ready skill cleanup.

Lingtai-AI By Lingtai-AI schedule Updated 6/14/2026

name: dev-guide-skill-stewardship description: > Nested lingtai-dev-guide reference for turning one-off experience into durable skills: when to write a skill vs leave it as notes, the router-vs-nested- reference pattern, distilling experience (归一) and session journals into triggered/executable SKILL.md files, de-privatizing and parameterizing local paths and human-specific details, a lightweight pre-publish benchmark/checklist, grooming shared-library candidates, and PR-ready skill cleanup. version: 1.0.0

Skill Stewardship

Nested lingtai-dev-guide reference. Read this after the top-level router sends you here when you are deciding whether to write a skill, distilling experience into one, or cleaning a skill up so it can ship in a PR.

This consolidates the skill-distillation meta-method (归一), the skill audit/ triage practice, the experience-to-skill side of session-journal handoff, the lightweight skill-benchmark checklist, and shared-library candidate grooming. It governs LingTai's skill hygiene; for generic skill-authoring mechanics (frontmatter spec, trigger syntax, file layout) cross-link to skills-manual rather than duplicating it here.

Core principle

A skill is the standard way to turn a repeated experience into something triggered, executable, verifiable, and maintainable. Write one when the technique would otherwise be re-derived ad hoc across sessions or agents — and only after it is de-privatized and lightly benchmarked. Skills that ship in this repo's preset tree must be parameterized: no private paths, no human-specific details, no secrets.

1. When to write a skill

Write a skill when:

  • the technique was not intuitively obvious and you would reference it again;
  • multiple agents/sessions keep re-implementing the same workflow with divergent quality (convergent discovery is the strongest signal — see the skill audit);
  • the pattern is broadly reusable, not a one-off or project-specific convention.

Do not write a skill for:

  • one-off solutions or single-incident narratives;
  • standard practices already documented elsewhere (link instead);
  • project-specific conventions — those belong in CLAUDE.md/repo docs;
  • mechanical constraints enforceable by a test/regex — automate, don't document.

If it is real but not yet skill-worthy, leave it as a session-journal entry or a shared-library candidate (§5) until the pattern repeats.

2. Routing vs nested-reference pattern

LingTai utility skills use progressive disclosure: a short router SKILL.md at the root plus focused nested references under reference/<topic>/SKILL.md.

  • Keep the router compact: a nested-reference catalog, a routing table, and cross-links. Detailed procedures live in the nested files, not the router.
  • A nested reference is parent-owned — it is a drill-down of its parent skill, not a standalone top-level skill. Begin each nested file by identifying itself, e.g. "Nested lingtai-dev-guide reference."
  • When you add a nested reference, update the parent's catalog and routing table in the same commit, and update any test that asserts the nested set (see tui/internal/tui/skill_files_test.go).

Prefer adding a nested reference to an existing router over creating a new top-level skill when the topic is a drill-down of an existing domain.

3. Distilling experience into a skill (归一)

The distillation loop turns scattered experience (chats, reports, code, daemon logs, knowledge entries, session journals) into a maintainable SKILL.md:

  1. Trigger. State the concrete situations that should load this skill — write them as the description "Use when…" triggers, in third person.
  2. Distill. Extract the reusable technique, not the narrative. One excellent example beats five mediocre ones; drop session-specific storytelling.
  3. Validate. Confirm any commands/computations actually run and produce the claimed result; fix or remove anything you cannot verify.
  4. Maintain. Note what would make the skill stale (an API change, a renamed file) so a future edit knows what to check.

Session journals feed step 1–2: a journal entry that records a reusable gotcha, decision, or procedure is the raw material for a skill. Promote it only when the pattern recurs; until then it stays a journal/handoff note. (For the journal format itself, defer to the kernel knowledge/psyche manuals — this reference only covers using journals as skill seeds.)

4. De-private and parameterize before publishing

Anything shipped in the preset skill tree (or proposed for the shared library) must be scrubbed:

  • Paths: /Users/<name>/...<your-lingtai-checkout> or ~/.lingtai-tui/....
  • People: named individuals → "the maintainer"; private project names → generic.
  • Secrets: tokens/keys/passwords → <REDACTED> or ${ENV_VAR} references.
  • Channels/IDs: Telegram chat IDs, emails, recipient lists → parameterized or removed.
  • PR/issue numbers: concrete numbers → examples only ("e.g. a small PR like #NNN").

It is fine to mention repo-relative paths and generic command examples; only private, machine-, or person-specific details must go.

5. Lightweight pre-publish benchmark / checklist

Before a skill ships, run a quick "pre-flight" — a benchmark/checklist, not a heavy framework:

  • YAML frontmatter parses; has name (letters/numbers/hyphens) and a description that starts with "Use when…" and lists triggers only (no workflow summary).
  • Document structure is scannable: overview/core principle, when-to-use, steps, related references.
  • Declared dependencies/cross-linked skills exist and are named correctly.
  • Any commands/snippets were actually executed and produce the claimed output (the skill-benchmark practice caught real API breakage this way).
  • De-privatization (§4) is complete.
  • For nested references: parent catalog + routing table + tests updated.

6. Shared-library candidate grooming

Not every reusable experience belongs in this repo's preset tree. Triage:

  • Repo dev-guide nested reference — developer/operator methodology for working on LingTai itself (this is where these three new references live).
  • Shared library candidate — broadly reusable agent behaviour that is not LingTai-dev-specific; groom it (de-private, benchmark) and propose it for the shared library rather than the preset tree.
  • Project/custom skill — domain-specific (heliophysics, nutrition, VC, etc.) or privacy-contaminated; keep it in the project, do not promote it.

When in doubt, prefer the smallest, most local home that still makes the skill discoverable; promote later when convergent reuse is demonstrated.

7. PR-ready skill cleanup

Bundle skill changes into a reviewable PR with:

  • the router catalog/routing-table edits in the same commit as the new/changed nested reference;
  • updated tests (tui/internal/tui/skill_files_test.go for nested-reference assertions) and a passing focused run;
  • a self-contained HTML explainer (see reference/pr-review-deliverables/SKILL.md).

Related references

  • skills-manual — generic skill authoring: frontmatter spec, trigger syntax, file layout, testing skills. Defer to it for mechanics; this reference covers LingTai-specific stewardship.
  • reference/pr-review-deliverables/SKILL.md — review gates and the HTML explainer for a skill-changing PR.
  • reference/contributing/SKILL.md — issue → worktree → PR → merge loop and the same-commit catalog/router/test rule.
Install via CLI
npx skills add https://github.com/Lingtai-AI/lingtai --skill dev-guide-skill-stewardship
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