Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-skillsnpx agentmods add skills/bilal140202/the-lord-of-the-skills/colbymchenry__codegraphWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/colbymchenry__codegraph)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/colbymchenry__codegraph"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/colbymchenry__codegraph/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/colbymchenry__codegraph"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/colbymchenry__codegraph.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00077 | $0.03008 |
| Opus 5 | $0.00039 | $0.01504 |
| Sonnet 5 | $0.00015 | $0.00602 |
| Haiku 4.5 | $0.00008 | $0.00301 |
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 9d 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: 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.
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-inclaudeCLI (the benchmark spawns realclaude -pruns). - 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.tsresolves it fromtree-sitter-wasmsautomatically. (Many languages: elixir, zig, ocaml, solidity, toml, yaml, …) - Absent → vendor a
.wasmintosrc/extraction/wasm/(likepascal/scala/lua) and add the token to the vendored branch in Step 4.
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.
- 9d ago First seen · 220 lines · 77 tokens per session scan A ba81accf3243
add-lang is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (4 stars, last pushed 6d 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.
Other skills, from other repositories
first-plan-lens-go
Stack lens para projetos Go. Use durante Discovery quando go.mod for detectado. Extrai padrões de layout (cmd/internal/pkg), error handling, context.Context, concurrency, code generation, build tags.
first-plan-lens-typescript
Stack lens para Node/TypeScript. Use durante Discovery quando package.json for detectado. Cobre Next.js, NestJS, Vite SPA, Express, Astro, Remix, Nuxt, plain Node, monorepos pnpm/turbo/nx.
first-plan-lens-php
Stack lens para PHP. Use durante Discovery quando composer.json for detectado. Cobre Laravel, Symfony, Slim, Hyperf, Laminas, raw PHP. Identifica PSR compliance, ORM, padrões de fila.
first-plan-lens-python
Stack lens para Python. Use durante Discovery quando pyproject.toml, setup.py ou requirements.txt for detectado. Cobre FastAPI, Django, Flask, Litestar, Celery workers, data apps, packaging src/ vs flat.
first-plan-lens-rust
Stack lens para Rust. Use durante Discovery quando Cargo.toml for detectado. Cobre binários, libs, async runtimes (tokio/async-std), error handling, web frameworks (axum, actix-web, rocket).
serpsmith
Publish SEO articles reliably across AI-agent runtimes.