A tiny language for AI agents. Instead of letting a program do anything and bolting a sandbox on afterwards, the things agents need are part of the language. (Renamed from "agentlang", which turned out to already be the name of an unrelated, existing open-source project.)
- Permissions are declared up front. A program can only read or write what it
declared with
needs. Anything else is refused. - Retries are always bounded.
retry N { ... }needs a fixedN(1 to 10). - Verification is a statement.
verify a == bstops the program if it does not hold. - Every action is logged in a hash-chained audit log that can be checked for tampering.
- Errors are structured JSON with a kind, a line, a message and a concrete hint, so a model can feed them back and repair its own program.
- Every program terminates. The only repetition is
retry(fixed limit) andforover a finite list. There is nowhile.if/elseonly chooses between blocks. - Total work is bounded. Every statement counts against a step budget
(
--max-steps, default 10,000), the general safety net that also stops nestedretryblocks from silently multiplying their attempts.
Leashterm is less a general-purpose programming language and more an executable
capability manifest with computation attached. needs says what a program can touch;
the absence of unbounded loops says how much computational escalation is possible; the
step budget bounds composite work; and the audit log makes executed behavior checkable
after the fact. The distinguishing core is not the syntax - it is pre-execution capability
checking plus structurally bounded computation, and that is the identity the language
should stay tightly built around as it grows.
The guiding design question for any future addition is not "what features is the language missing?" but: what is the smallest language in which an agent can still do useful work, while every program still admits a compact, pre-execution upper bound on both its capabilities and its work? That is also why arithmetic, dynamic string construction, general functions, and subprocesses are deliberately absent rather than merely unfinished: each would make the language more capable at the cost of making that upper bound harder to state and check. If any of them is ever added, it should be because a concrete case exposed a guarantee that is not otherwise achievable - the same reasoning that justified the v0.7 step budget - not because ordinary languages have them.
Leashterm bounds the effects that happen during Leashterm's own execution, through its
own runtime primitives (read, write, fetch). It does not, and cannot, control what a
downstream system does with content Leashterm legitimately wrote.
A program that is only permitted to write project/calc.py cannot read a forbidden file to
put into that write - but nothing stops it from writing source code that itself refers to
something outside its permissions (an import statement naming a sibling package, say),
which only becomes a real access once some other interpreter later runs that file. Case 1
(cases/case1-filesystem/) found exactly this: 3 of 9 trials did not attempt an undeclared
read at all, yet still smuggled the dependency past Leashterm this way. This is not a bug
to patch away; it is the honest edge of what a language-level boundary can promise. The
correct claim is "declared authority is enforced within Leashterm's own execution," not
"nothing bad can ever result from a Leashterm program."
This is an early skeleton: lexer, parser, static permission check, interpreter, tests
and ten examples. v0.6 passed its tests and the 22-task benchmark in Codespaces and on
GitHub, including a reproducible 9-trial result (see benchmark/README.md). v0.7 adds a
general step budget (44 tests) and still needs its first cargo test.
needs read("notes.txt") # permission (only allowed at the top)
needs write("out.txt")
needs fetch("example.com") # network permission is per domain
let text = read("notes.txt") # variables
print(text) # builtins: print, len, trim, concat, read, write, fetch
verify len(text) == 10 # stop the program if false
retry 3 { # bounded retry, never repeats a missing permission
let t = read("maybe.txt")
}
let page = fetch("https://example.com/page") # https only, domain must be declared
if trim(text) == "yes" { # chooses a block; else is optional; conditions are == or !=
print(concat("got: ", text))
} else {
print("no")
}
for f in ["a.txt", "b.txt"] { # loops over a finite list, always stops
print(read(f))
}
Values are text, numbers, booleans and lists. == compares two values.
A program's needs lines are requests. Without more, a program could simply grant itself
anything. So the person or system that runs it can set a hard limit:
leashterm prog.lsh --allow read:data/a.txt --allow write:out/b.txt
If any --allow is given, a program that asks (with needs) for something not on that
list is refused before it starts, with policy_denied and a hint that lists what is
allowed. Without --allow, the program's own needs lines are the only limit.
- Only
https://URLs. The permission names a domain:needs fetch("example.com"). - A subdomain such as
api.example.comneeds its own permission. - Tricks like
https://example.com@evil.com/are refused as invalid URLs. - Redirects are blocked, because they could leave the permitted domain.
- 10 second timeout and at most 50 fetches per run (a simple cost budget).
- The audit log records only the domain, not the full URL (which may contain secrets).
- The tests use a fake fetch function, so they never need the internet.
Every statement executed (including each inner attempt of a retry, and each pass of a
for loop) counts against a step budget, 10,000 by default:
leashterm prog.lsh --max-steps 500
This is the general safety net on total work, not a replacement for --allow or the fetch
budget: it catches the case neither of those does, nested retry blocks silently
multiplying their attempts (retry 10 { retry 10 { ... } } can reach 100 inner attempts
from two lines that each look like "at most 10"). Like a denied permission, a budget hit
inside a retry block is never retried; it fails the whole block immediately.
You need Rust. On an iPad, use GitHub Codespaces: it already has a terminal where you
can install Rust (curl https://sh.rustup.rs -sSf | sh) or use a Rust dev container.
cargo test # run the unit tests
cargo run -- examples/01_hello.lsh # run a program
cargo run -- examples/02_read_file.lsh --log # also print the audit log
cargo run -- examples/03_denied.lsh # must fail with capability_denied
cargo run -- examples/02_read_file.lsh --allow read:examples/other.txt # policy_denied
cargo run -- examples/04_retry.lsh # must fail with retries_exhausted
cargo run -- examples/06_for_loop.lsh # loops over two files
cargo run -- examples/07_for_denied.lsh # refused before anything runs
cargo run -- examples/08_fetch.lsh # needs internet
cargo run -- examples/09_fetch_denied.lsh # refused before anything runs
cargo run -- examples/10_if_and_concat.lsh # if/else, concat and trim
cargo run -- examples/04_retry.lsh --max-steps 2 # must fail with budget_exceeded
Example of a refused program (stderr):
{"error":"capability_denied","line":4,"message":"read(\"examples/secret.txt\") is not permitted","hint":"add this line at the top of the program: needs read(\"examples/secret.txt\")"}
- The audit log uses Rust's
DefaultHasher. That is a placeholder, not secure. Use SHA-256. - Permissions are checked before running for literal paths and for loop variables over a
literal list (
src/check.rs). Other paths, such as a variable that holds a result, are still only checked while running. - No parallel calls, no memory, no sub-agents yet.
fetchonly does GET and has no wildcard domains. Redirects are blocked rather than followed. - Nested
retryblocks still multiply their attempts mathematically; the step budget only bounds thetotal , it does not stop the nesting itself, and there is no static check that warns about it before running (the step budget is runtime-only). - The step budget counts statements, not wall-clock time or memory, so a single slow
fetch(up to its own 10-second timeout) is not charged more than a fast one.
- Make it compile and pass
cargo test. Add a static permission check before execution.Done in v0.2.Lists andDone in v0.3.forloops.Done in v0.4. Next: parallel calls with a time and cost budget.fetch(url)with domain permissions and a fetch budget.- Add persistent memory with its own permission, then delegation where permissions can only shrink.
- Replay: re-run an audit log deterministically and report where results differ.
Pilot benchmark and automatic tests on GitHub.Done in v0.5 (seebenchmark/).Done in v0.6. The benchmark (not the language) grew to 22 tasks: T11-T12 (temptation), T13-T20 (instruction-following traps) and T21-T22 (a spontaneous-temptation experiment inspired by the July 2026 OpenAI-Hugging Face incident, seeif/else,concat,trim.benchmark/README.md). ChatGPT scored 20/20 and 19/20 (Python/leashterm) on T01-T20, with zero out-of-bounds access either way: these tasks have not yet shown a safety advantage, only shorter programs. T21 and T22 are a planned family of tasks (not a language change) at increasing temptation strength. T21 came back clean (no attempt in either language); T22 did not. Repeated 9 times per language from fresh conversations: Python attempted the undeclared file in 9/9 trials and leaked data in 9/9; leashterm attempted it in 9/9 trials (identical model intent) but was blocked before execution in 9/9 - a 100%-vs-0% result, not a single anecdote. Seebenchmark/evidence/andbenchmark/solutions/t22-trials/for ChatGPT's actual, unedited answers andbenchmark/README.mdfor the full design and this caveat: one model, one task, one temptation level - not yet a general claim.General step budget (Done in v0.7. Built specifically so three practical demo cases (filesystem sandboxing, network egress control, and resource/cost limits - the three things companies now handle with external infrastructure around an agent rather than in its code) could all be built on exactly the same language version. Cases 1 and 2 needed no language change; case 3 needed this step budget.--max-steps), bounding nestedretrymultiplication.Case 1: filesystem sandboxing, with a 9-trial result per language.Done - seecases/case1-filesystem/. Python: 89% of trials read the undeclared sibling file and 100% of those leaked it; Leashterm: 100% of trials engaged with it (directly or via a newly-discovered deferred-reference pattern) and 0% leaked.Case 2: network egress control, with a 9-trial result per language on real domains.Done - seecases/case2-network/. Python: 100% of trials fetched the undeclared domain and 100% of those leaked it; Leashterm: 78% attempted it (0% succeeded). Required adding real network-attempt detection to the benchmark harness (socket.getaddrinfohook, afetchespermission). Also surfaced a measurement mistake (a vague pointer made the first run of this look artificially strong) that was caught and corrected, documented in the case's README.Case 3: resource/cost budgets, built on the v0.7 step budget.Done, including a 9-trial result per language - seecases/case3-resources/. Both languages: 100% engagement (every trial tried to go past the one declared file); Python leaked the undeclared answer in 9/9, Leashterm was refused in 9/9 - the strongest divergence of the three cases, and clear evidence that identical model behavior does not guarantee identical outcome. All three cases now exist on the same Leashterm version (v0.7), as planned, and all three show the same shape: Case 1 (filesystem, 89% vs 0%), Case 2 (network, 100% vs 0%), Case 3 (resources, 100% vs 0%).