add-lang

A workflow for adding support for a new programming language to CodeGraph using tree-sitter, a parser that turns source code into a structure the tool can analyse.

In plain words
What is it for?
Use it to add languages such as Lua, Elixir, Zig, or OCaml, test extraction on real repositories, benchmark retrieval value, and update documentation.
Why use it?
It covers the full path from connecting the language grammar to checking extracted code symbols and measuring whether the support helps an AI agent.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/lagrahhn/codegraph-branch/add-lang
Any agent
npx skills add lagrahhn/codeGraph-branch --skill add-lang
Clone the repo
git clone --depth 1 https://github.com/lagrahhn/codeGraph-branch

Made for: Claude Code, Codex.

Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,008 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00077 $0.03008
Opus 5 $0.00039 $0.01504
Sonnet 5 $0.00015 $0.00602
Haiku 4.5 $0.00008 $0.00301

Measured 2d ago against content hash ba81accf3243, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

add-lang scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

classes/structs, imports, enums; or `curl` a raw file from a known repo), then:
Origin

This is a copy

100% identical to add-lang — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.claude/skills/add-lang/SKILL.md · 220 lines

How it starts

The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Add a language to CodeGraph

Wire a new tree-sitter language into codegraph's extraction pipeline, prove it extracts real symbols on popular repos, and prove it beats no-codegraph for an agent. Runs fully autonomously — pick repos, benchmark, update docs, then report. Never commit, push, publish, or tag (house rule); leave all changes for the user to review.

The argument is the language token used throughout the Language union, e.g. lua, elixir, zig. If none was given, ask which language. Use the lowercase single-token form everywhere (csharp, not c#).

Prerequisites

  • Run from the codegraph repo root. node, git, gh, and a logged-in claude CLI (the benchmark spawns real claude -p runs).
  • The benchmark uses the local dev build — Step 8 builds + links it on PATH.

Workflow

Copy this checklist and work through it in order:

- [ ] 1. Resolve language; bail early if already supported (just benchmark)
- [ ] 2. Find a grammar + health-check it (ABI / heap corruption)
- [ ] 3. Discover the grammar's AST node types (dump-ast.mjs)
- [ ] 4. Wire the language (4 files; sometimes a 5th core touch)
- [ ] 5. Build + verify-extraction loop until PASS
- [ ] 6. Add extraction tests; make them green
- [ ] 7. Auto-pick 3 popular repos by size tier; add to corpus.json
- [ ] 8. Benchmark all 3: extraction + with/without A/B
- [ ] 9. Update README + CHANGELOG
- [ ] 10. Report; do NOT commit

Step 1 — Resolve + short-circuit

Check whether the language is already wired: look for the token in the LANGUAGES const (src/types.ts) and the EXTRACTORS map (src/extraction/languages/index.ts). If it is already supported (e.g. typescript, rust), skip Steps 2–6 and go straight to benchmarking (Steps 7–8) to validate/measure it — note in the report that no code changed.

Step 2 — Find a grammar, then health-check it

ls node_modules/tree-sitter-wasms/out/ | grep -i <lang>   # csharp -> c_sharp
  • Present → likely off-the-shelf; grammars.ts resolves it from tree-sitter-wasms automatically. (Many languages: elixir, zig, ocaml, solidity, toml, yaml, …)
  • Absent → vendor a .wasm into src/extraction/wasm/ (like pascal / scala / lua) and add the token to the vendored branch in Step 4.

Read the full file on GitHub · 220 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 220 lines · 77 tokens per session scan A ba81accf3243

Subscribe to this mod's changes

add-lang is a skill published in the GitHub repository lagrahhn/codeGraph-branch (2 stars, last pushed 1mo ago), licensed MIT. It adds 77 tokens to every session and 3,008 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to add-lang, differing in 0 lines, and is treated as a copy.

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