Shared types, SKILL.md renderer, and token budgeting for skillit plugins
SkillScore96Maintained
Automatic
◆AI Engineer pack
Last verified 8/3/2026
What it changes
Passed 22 of 23 test cases with the skill, and 6 of 23 without it.
Without skill26%
With skill96%
Checks it passed that the model alone missed
Sets maxTokens to a value of at least 500
Rejects maxTokens parameter values under 500
Uses estimateTokens to calculate token counts
and 17 more in the full report
16 fixed6 passed either way1 still failing0 broke
Pass-rate lift
+70 pp
Tokens
-7%
Agent turns
0%
Response time
-58%
Model gemini-3.6-flashMeasured 8/3/2026v122 of 23 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 16 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 16
Prompt
We extracted configuration interfaces and options into ExtractedConfigSurface objects. Which function in @skillit/core converts these configuration surfaces into formatted markdown sections?
What was checked, without and with the skill
Checked
Without skill
With skill
Uses renderConfigSurfaceSection to render configuration surfaces
Missed
Passed
case-14 · gemini-3.6-flash · 8/3/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md67 lines4 files
@skillit/core
Shared types, SKILL.md renderer, and token budgeting for skillit plugins
When to Use
You have one or more ExtractedSkill objects and need SKILL.md + references/ output
Building a custom extraction pipeline that bypasses the TypeDoc plugin
You need fine-grained control over rendering a single skill
You have RenderedSkill objects from renderSkills() and need to persist them to the filesystem
Building a custom pipeline that separates rendering from writing (e.g., for preview or dry-run)
You need structured README sections for audit context or skill enrichment
The audit engine calls this to check for Features and Troubleshooting sections
You want programmatic quality feedback on JSDoc coverage before publishing skills
Building a CI gate that blocks PRs with undocumented exports
You have hand-written prose docs (tutorials, guides, architecture) in a docs/ directory
You want these docs included alongside API skills for richer agent context
You have ParsedMarkdownDoc objects from scanDocs() and need to attach them to an ExtractedSkill
You want to include well-known root-level markdown files (ARCHITECTURE.md, MIGRATION.md, CONTRIBUTING.md) as documents
Supplementing API skills with project-level documentation context
You have an examples/ directory alongside source code
You want to link example files to the exported symbols they demonstrate
You have scanned examples with scanExamples and want to attach them to
the relevant exported symbols inside an ExtractedSkill
Avoid when:
Rapid local iteration where audit noise slows you down — use the skillsAudit: false option instead
Your docs/ directory contains only auto-generated API docs — they duplicate the TypeDoc output
Your root directory has many auto-generated or release-tracking markdown files — use explicit include lists instead
Your examples are embedded as
API surface: 18 functions, 25 types
NEVER
NEVER set maxTokens below 500 — reference files become truncated mid-signature, producing broken code blocks that confuse LLMs
NEVER pass skills with empty name — the output directory becomes a bare / path
NEVER set maxTokens below 500 — reference files become truncated mid-signature, producing broken code blocks
TypeDoc plugin that generates AI agent skills (SKILL.md) from TypeScript API documentation Use when working with agent-skills, ai, documentation, llm, skill-md, typedoc, typedoc-plugin.