AGENT SKILL

ast-codegen-patterns

暂无简介

License 许可
Apache-2.0
最近更新
2026-11-14
Stars
★ 13
Forks
2

03 SKILL.md 正文

/ast-codegen-patterns

When to Use

  • Regenerate source from a modified AST (after [[babel-ast-transform]] or [[estree-ast-spec]] walker)
  • Format-preserving reprints: preserve whitespace/comments in unmodified subtrees
  • Round-trip pipelines: parse → mutate → generate → diff
  • Custom code generation: emit domain-specific patterns from data models

Do NOT use for

  • Full Babel transform pipelines (use [[babel-ast-transform]] which includes generate)
  • TypeScript codegen from scratch (use [[ts-morph-refactor]] for type-safe generation)

ESTree → source (escodegen)

import escodegen from 'escodegen'
import { parse }  from 'acorn'

const source = `
const arr = [1, 2, 3]
const doubled = arr.map(x => x * 2)
`

const ast = parse(source, { ecmaVersion: 2022, sourceType: 'module' })

// Mutate AST: rename 'doubled' → 'multiplied'
function rename(node, from, to) {
  if (!node || typeof node !== 'object') return
  if (node.type === 'Identifier' && node.name === from) node.name = to
  for (const key of Object.keys(node)) rename(node[key], from, to)
}
rename(ast, 'doubled', 'multiplied')

const output = escodegen.generate(ast, {
  format: {
    indent:    { style: '  ' },
    quotes:    'single',
    semicolons: true,
  },
  comment: true,   // preserve comments from original
})

console.log(output)
// const arr = [1, 2, 3];
// const multiplied = arr.map(x => x * 2);

Source map–aware generation

import escodegen from 'escodegen'
import { SourceMapConsumer } from 'source-map'

const { code, map } = escodegen.generate(ast, {
  sourceMap:         'input.js',
  sourceMapWithCode: true,
  format: { compact: false },
})

// map is a SourceMapGenerator — serialize for output
const sourceMapString = map.toString()
const codeWithMap = code + '\n//# sourceMappingURL=data:application/json;base64,'
                       + Buffer.from(sourceMapString).toString('base64')

Manual AST builder (no parser needed)

// Build `export const VERSION = "1.0.0"` from scratch
function buildVersionExport(version: string) {
  return {
    type: 'ExportNamedDeclaration',
    declaration: {
      type: 'VariableDeclaration',
      kind: 'const',
      declarations: [{
        type: 'VariableDeclarator',
        id:   { type: 'Identifier', name: 'VERSION' },
        init: { type: 'Literal',    value: version, raw: JSON.stringify(version) },
      }],
    },
    specifiers: [],
    source: null,
  }
}

const program = {
  type: 'Program',
  body: [buildVersionExport('1.0.0')],
  sourceType: 'module',
}

console.log(escodegen.generate(program))
// export const VERSION = '1.0.0';

Round-trip codemod helper

import { parse }   from 'acorn'
import escodegen   from 'escodegen'

export function codemod(
  source:  string,
  mutate:  (ast: any) => void,
  options: escodegen.GenerateOptions = {}
): string {
  const ast = parse(source, {
    ecmaVersion: 2022,
    sourceType:  'module',
    onComment:   (block, text, start, end) => {
      // attach comments to nearest node for escodegen to reprint
    },
  })
  mutate(ast)
  return escodegen.generate(ast, {
    comment: true,
    format: { indent: { style: '  ' }, ...options },
  })
}

Anti-Fake-Pass Checklist

❌ escodegen.generate on Babel AST → Babel adds non-ESTree nodes; strip them first
❌ comment: false → all comments lost in round-trip
❌ Mutating raw node.loc values → code generation uses loc for source maps; corruption
❌ compact: true in a codemod → diffs become unreadable one-liners
❌ Manual AST missing 'raw' field on Literal → some generators produce undefined
❌ sourceMap: 'filename' must match the original filename exactly or stack traces break

04 同仓库更多 Skills

Horonomos-laps
Horonomos-laps/Yana-AI

openai--sentry--sentry

Use when the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.

★ 13
Horonomos-laps
Horonomos-laps/Yana-AI

ito-basket-compare

Compare Itô prediction-market baskets against a user's knowledge base, portfolio notes, financial context, watchlist, or research thesis. Use for read-only basket comparison and gap analysis without investment advice or live trading.

★ 13
Horonomos-laps
Horonomos-laps/Yana-AI

implementing-network-traffic-baselining

Build network traffic baselines from NetFlow/IPFIX data using Python pandas for statistical analysis, z-score anomaly detection, and hourly/daily traffic pattern profiling

★ 13
Horonomos-laps
Horonomos-laps/Yana-AI

detecting-evasion-techniques-in-endpoint-logs

Detects defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.

★ 13
Horonomos-laps
Horonomos-laps/Yana-AI

implementing-microsegmentation-with-guardicore

Implementing microsegmentation using Akamai Guardicore Segmentation to map application dependencies, create granular network policies, visualize east-west traffic flows, and enforce least-privilege communication between workloads across data centers and cloud.

★ 13
Horonomos-laps
Horonomos-laps/Yana-AI

ramdisk-tmpfs-patterns

暂无简介

★ 13