# Show HN: Aict – Unix coreutils that output XML/JSON, built for AI agents > Source: > Published: 2026-07-15 13:39:54+00:00 **Unix coreutils with XML/JSON output — built for AI agents, not humans.** [Install](#install) · [Quick start](#quick-start) · [All tools](#tools) · [MCP server](#mcp-server) · [Claude Code](#claude-code-integration) · [Token cost](#token-cost) · [Benchmarks](#benchmarks) · [Contributing](/synseqack/aict/blob/master/CONTRIBUTING.md) AI agents run `ls` , `grep` , and `cat` and get back **human-readable plaintext**. Then they spend tokens parsing column positions, guessing field widths, and handling inconsistent formats. This is fragile and wasteful. ``` -rw-r--r-- 1 user staff 2048 Apr 6 10:00 main.go ← which column is size? -rw-r--r-- 1 user staff 1024 Apr 6 10:00 utils.go ← what's the language? drwxr-xr-x 5 user staff 160 Apr 6 10:00 internal ← is this a directory? ``` `aict` reimplements 33 Unix tools with **structured output** the agent can read directly — no parsing required. ``` bash $ aict ls src/ ``` Every field is labeled. Paths are always absolute. Timestamps are Unix integers. Language and MIME type are detected automatically — zero parsing needed. ``` brew tap synseqack/aict brew install aict ``` This installs `aict` plus shell completions for bash and zsh. The MCP server is built in: `aict mcp` . ``` go install github.com/synseqack/aict@latest git clone https://github.com/synseqack/aict cd aict go build -o aict . ``` Verify install:`aict --help` should list all available tools. ``` # Default: XML output (best for AI agents) aict ls src/ aict grep "func" . -r aict cat main.go aict diff old.go new.go # JSON output aict ls src/ --json # Plain text (same as the original Unix tools) aict ls src/ --plain # Enable XML globally for all aict calls export AICT_XML=1 ``` 33 tools across 6 categories. Every tool supports `--xml` (default), `--json` , and `--plain` . | Category | Tools | |---|---| File inspection | `cat` `head` `tail` `file` `stat` `wc` | Search & compare | `ls` `find` `grep` `diff` | Path utilities | `realpath` `basename` `dirname` `pwd` | Text processing | `sort` `uniq` `cut` `tr` `sed` `awk` | Data & archives | `jq` `tar` | System & environment | `env` `system` `ps` `df` `du` `checksums` `md5sum` `sha1sum` `sha256sum` | Additional: `git` (status, diff, log, ls-files, blame) · `completions` (bash/zsh/fish) · `doctor` (self-diagnostic) All tools follow the same conventions: | Field | Convention | |---|---| | Paths | Always absolute (`absolute` attr) | | Timestamps | Unix epoch integers + `_ago_s` companion | | Sizes | Bytes (`size_bytes` ) + human-readable (`size_human` ) | | Booleans | `"true"` / `"false"` strings | | Errors | `` elements — never stderr | | Empty results | Valid XML with zero counts, never an error | `aict mcp` exposes all tools as callable MCP functions via stdio transport. AI assistants call them natively — no shell wrapping needed. The MCP server is a subcommand of the main binary. **Configure Claude Desktop** (`~/.config/claude/claude_desktop_config.json` ): ``` { "mcpServers": { "aict": { "command": "aict", "args": ["mcp"] } } } ``` If `aict` is not in PATH, use its full path: ``` { "mcpServers": { "aict": { "command": "/usr/local/bin/aict", "args": ["mcp"] } } } ``` Add to `~/.claude.json` : ``` { "mcpServers": { "aict": { "command": "aict", "args": ["mcp"] } } } ``` Once connected, Claude Code can call `ls` , `grep` , `diff` , and all other tools as native functions with typed arguments and structured JSON results. Honest numbers first: **aict output costs 1.1–7.8× more tokens per task than terse GNU output** (measured with tiktoken `o200k_base` ). What those tokens buy: fewer round-trips and zero parsing ambiguity. Where plaintext needs 2–4 chained calls (`ls` then `file` for languages, `find` then `stat` per hit), aict answers in one. | Task | GNU | aict | Tokens (GNU → aict) | |---|---|---|---| | List dir with size/type/language | 2 calls | 1 call | 246 → 820 · 3.3× | | Read file + line count + type | 3 calls | 1 call | 173 → 274 · 1.6× | Find `.go` files with size/mtime | 4 calls | 1 call | 47 → 367 · 7.8× | | Grep with file/line/context | 1 call | 1 call | 141 → 326 · 2.3× | | Diff with change types | 1 call | 1 call | 167 → 192 · 1.2× | Every extra plaintext call is a full agent turn — model inference, tool-call overhead, and intermediate output all land in the context window anyway, none of which the token counts above include. And in this very benchmark, `file(1)` misidentified a Go source file as "C source"; aict labeled it `go` . In a live agent eval (opencode, same task 3× per toolchain), the aict-equipped agent generated **~46% fewer output tokens** (median 265 vs 487) and was correct 3/3 — the GNU-equipped agent shipped a flawed report in the run where it trusted `file(1)` 's language detection. See [ benchmarks/TOKENS.md](/synseqack/aict/blob/master/benchmarks/TOKENS.md) for both methodologies; reproduce with `go run ./cmd/tokenbench` .Use `--plain` when you only need raw content. aict trades some speed for semantic richness (language detection, MIME typing, absolute paths). The overhead is intentional. Startup cost is ~3.6 ms per invocation. | Tool | GNU | `--plain` | `--xml` | Notes | |---|---|---|---|---| `diff` (1000 lines) | 0.9 ms | 1.9 ms · 2.1× | 2.1 ms · 2.4× | ✅ Myers O(ND) | `wc` (100k lines) | 6.1 ms | 16 ms · 2.6× | 17 ms · 2.7× | ✅ | `awk` (10k lines) | 4.1 ms | 12 ms · 2.9× | 11 ms · 2.6× | ✅ | `sed` (10k lines) | 3.3 ms | 14 ms · 4.2× | 16 ms · 4.9× | ✅ | `find` (deep tree) | 1.9 ms | 13 ms · 6.8× | 15 ms · 8.0× | ✅ | `ls` (1000 files) | 4.0 ms | 51 ms · 12.9× | 70 ms · 17.7× | MIME+lang detection per file | `cat` (100k lines) | 1.4 ms | 24 ms · 16.4× | 31 ms · 21.6× | line-by-line scan + encoding detect | `grep` (100k lines) | 1.3 ms | 119 ms · 88× | 130 ms · 96× | Go regexp vs GNU SIMD | Medians from 5 runs on Linux/amd64. See [ benchmarks/](/synseqack/aict/blob/master/benchmarks) for methodology and `make bench` to reproduce.Use `--plain` to skip enrichment when you only need raw content. **Why XML and not JSON by default?** XML attributes are denser in a context window. `` is shorter than `{"size":1024,"lang":"go"}` . Use `--json` if you prefer JSON — the structure is identical. **Why not pipe GNU tools to jq?** `ls` , `cat` , `stat` , `find` , `diff` , and `wc` don't output JSON. `jq` can't help with them. aict provides structured output for the entire toolchain, not just grep. (aict also ships its own `jq` for querying JSON files with path expressions.) **How does this compare to ripgrep?** ripgrep is much faster for pure search. aict grep adds language detection, MIME type, and a consistent output format shared with every other tool. Use ripgrep for speed-critical search; use aict when the agent needs structured context. **How does this compare to eza / lsd?** eza and lsd are better `ls` for humans — great colors and formatting. aict outputs data structures, not formatted tables. They're solving different problems. **Does it work on Windows?** `ls` , `cat` , `stat` , `wc` , `find` , `diff` , `grep` , `head` , `tail` , `sort` , `uniq` , `cut` , `tr` , `sed` , `awk` , `jq` , `tar` , `checksums` , `df` , and path utilities work on Windows. `system` is Linux/macOS; `ps` is Linux-only (it reads `/proc` ). Unsupported platforms get a structured `` element, never a crash. **Is this safe to run in a sandboxed environment?** Yes. aict is strictly read-only. No network requests (MIME detection uses the Go stdlib, not HTTP). No telemetry. No data collection. It only reads paths you explicitly pass to it. **How many dependencies does it have?** One: the official [MCP Go SDK](https://github.com/modelcontextprotocol/go-sdk), used only by the `aict mcp` subcommand. All 33 tools and every internal package are pure Go standard library — enforced as a hard constraint in [AGENTS.md](/synseqack/aict/blob/master/AGENTS.md). Bug reports, feature requests, and PRs are welcome. See [CONTRIBUTING.md](/synseqack/aict/blob/master/CONTRIBUTING.md) for guidelines, code style, and the tool implementation pattern. Issues tagged [ good first issue](https://github.com/synseqack/aict/issues?q=label%3A%22good+first+issue%22) are a good place to start. [MIT](/synseqack/aict/blob/master/LICENSE) — built entirely by AI tools, for AI tools.