IO Harness
A Rust agent harness that runs AI agents from a typed task contract to a checked result.
The shared engine every initorigin app (io-cli, io-studio) and io-eval build on.
Type: Rust library crate
Stack: Rust · cargo · tokio · rusqlite · rmcp · own HTTP+SSE provider client
License: Apache-2.0
Status: Pre-release. v0.1 shipped the single-agent file-edit loop (filesystem tool, OpenRouter provider, deterministic verify, rusqlite audit). v0.2 adds step/time/cost budgets, retry with escalation, a full trace, resumable runs, and execution-based verification that compiles the produced file so a substring stub cannot pass. v0.3 adds repository-wide work — grep and find tools over a workspace and multi-file edits in one run — and two more providers (Anthropic and OpenAI) behind the same provider-agnostic surface, selected at run construction. v0.4 adds the permission boundary: a layered policy over reads, writes, and command execution, enforced in the tool layer rather than the prompt, plus a human-approval gate that can approve, rewrite, remember, deny, or defer a decision until after the process has exited. v0.5 adds agent composition with containment: a parent decomposes a task and spawns contained sub-agents (100+ concurrently) over one shared workspace and trace, composing their results back; a child inherits its parent's policy and can only narrow it, and the whole tree runs under one aggregate spend ceiling no spawned task can raise.
Capabilities
- Task contract — goal, constraints, expected output, success criteria
- Context construction — feed the model only relevant, current, trusted info
- Tool layer — narrow, typed actions the agent invokes
- Orchestration loop — observe, reason, act, check, stop
- State and memory — progress, intermediate results, decisions (rusqlite)
- Verification layer — tests, schemas, read-backs confirm the task is done
- Permissions and guardrails — what the agent may access, change, send, spend
- Recovery and retry — retries, fallbacks, replanning, escalation
- Stop conditions and budgets — cap steps, time, cost, retries, risky actions
- Observability and tracing — record prompts, decisions, tool calls, cost
- Human approval layer — review before sensitive or irreversible actions
- Providers — OpenRouter first, then Anthropic and OpenAI (own HTTP+SSE client)
- Agent composition — spawn and nest many agents (100+) with shared context
- Long-running autonomous tasks — 24h+ with no user input
- Ephemeral local code-exec sandboxes — write, run, capture, destroy
- Built-in tools — filesystem, git, grep, find
- Office and document tools — Word/Excel/PowerPoint/PDF create/edit/delete, PDF watermark, PDF form fill, OCR, barcode/QR read and generate
- Media — image and video passthrough when the model supports it
- Extensibility — MCP (rmcp), plugins, skills
See docs/CAPABILITIES.md for detail and docs/CONTRACT.md for the public contract.
Usage (v0.4)
Hand the harness a task contract; it runs the loop, verifies the result, records
every step to rusqlite, and stops on success or a budget. A single-file task uses
the filesystem tool; a workspace task lets the agent grep/find across a
repository and edit several files. Pick any of three providers at construction.
Everything else in Capabilities is roadmap.
1. Add the crate
[]
= "0.3"
= { = "1", = ["rt-multi-thread", "macros"] }
Upgrading from 0.2: TaskContract::new, run, resume, and the single-file
loop are unchanged, so existing callers keep compiling. New in 0.3:
TaskContract::workspace, the grep/find/read_file tools, the
EachCompilesRust / WorkspaceTestPasses verifications, and the Anthropic /
OpenAi providers. If you implement Provider yourself, note it gained a
defaulted name() method (override it to label your provider in the trace — no
change required to keep compiling). A 0.2 rusqlite database is migrated in place
on open (a provider column is added; a 0.2 binary still reads it).
2. Choose a provider
Each provider reads its own key + model slug from the environment; credentials are never logged, and no default model is guessed. Selecting a provider is just constructing a different one — the task contract does not change.
# OpenRouter
# Anthropic
# OpenAI
use ;
let provider = from_env?; // or:
let provider = from_env?; // or:
let provider = from_env?;
// ...then hand `&provider` to `run` — nothing else changes.
3. Run one file-edit task, bounded and verified by execution
use Duration;
use ;
async
4. Run a repository task: grep, find, and multi-file edits
Give the agent a workspace root instead of one file. It can grep file contents
(regex or substring), find files by name/path glob, read_file to inspect
what it found, and write_file to edit several files — all confined to the root
(a .. or absolute path that escapes is refused). Verification spans the set:
WorkspaceTestPasses compiles the edited files together with a test, so the run
only succeeds when the whole set is correct.
use ;
let contract = workspace;
let result = run.await?;
println!;
The grep/find tools skip .git, target, and node_modules. Use
Verification::EachCompilesRust(files) when each edited file only needs to
compile on its own.
Execution-based verification
Content checks (FileContains, FileEquals) confirm the file says the right
thing but not that it works — the 0.1 live run passed FileContains("fn hello")
by writing the literal string fn hello, which does not compile. v0.2 adds gates
that run the artifact:
Verification::CompilesRust— passes only if the file compiles (rustc --crate-type lib).Verification::RustTestPasses { test_src }— appendstest_srcand passes only if the test binary passes.
Compilation runs locally in a throwaway temp dir (removed afterwards) and touches no network.
Trace and resume
Every step's prompt, decision, tool call, and token usage is persisted. Read the full trace back, and resume an interrupted run under its original id instead of restarting:
use ;
// After a crash or a hit budget, continue the same run from where it stopped.
let store = open?;
let result = resume.await?;
for step in store.steps?
Or run it live end to end: cargo run --example edit_file.
Permissions and approval (v0.4)
A Policy is a stack of named layers plus a per-action default. It is evaluated
deny-first across the whole stack: a deny in any layer beats an allow in any
other, so a layer can add capability but can never re-allow what a layer beneath
it denied.
use ;
let policy = default // reads open, writes ask, secrets denied
.layer
.allow_read
.deny_read
.deny_write;
let result = run_with.await?;
// Why was that refused? Same function the tool layer enforces with.
let verdict = policy.explain;
println!;
The default is permissive. A caller who passes no policy — plain run() —
gets no enforcement and the exact 0.3.0 behaviour. The boundary is opt-in. This
is a deliberate trade-off for backward compatibility, not an oversight.
What asks, what is refused
Policy::default() sets the tiers, following the same shape Claude Code uses:
| Action | Default | Note |
|---|---|---|
| Read | allow | .env, *.pem, id_rsa, id_ed25519, *.key denied outright |
| Write | ask | including overwriting a file the path rules already allow |
| Exec | ask | rustc and <test-binary> allowed, so verification works |
A denied action never reaches the approver — it is refused and reported to the model as a tool result it can adapt to, and the refusal consumes a step, so a model retrying it reaches the step cap rather than looping. Only the ask tier prompts.
The approver
use ;
The trait is object-safe (Box<dyn Approver>) and the future may stay pending
indefinitely — the run waits rather than timing out. Decision::Approve can
also carry a rewritten action (modified) or rules to remember for the rest
of the run. Both are re-checked against the policy: an approval cannot move an
action across a deny, and a remembered allow cannot override one.
Remembered rules come back on RunResult::remembered for you to persist.
Built-ins: ApproveAll, DenyAll, StdinApprover.
Deferring past the end of the process
match result.outcome ;
The pending action is persisted with the content the human was shown, so the resumed action is exactly the one approved. The policy is re-checked on resume, so a deny that landed while it waited still holds.
Sharing one policy between apps
Policy is serde-serializable, so io-cli and io-studio read the same format
and neither writes its own parser. Compose layers with merge:
let effective = shared_base.merge;
The recommended convention is user base → project layer → app overlay, each app keeping its own config file over a shared base. The crate composes a stack it is handed; it does not discover config files — locations and precedence are the adopting app's responsibility. Because denies are absolute across layers, a shared base stays trustworthy no matter what an app stacks on top.
Run it live: cargo run --example policy_run.
Agent composition and containment (v0.5)
A single loop does work one step wide. For large or parallelisable tasks, a parent agent decomposes the work and spawns sub-agents — up to 100+ at once — each running the same observe/reason/act/verify/stop loop over the same workspace and the same trace. A child's result composes back so the parent continues from what it produced, and children may nest.
Sub-agents are opt-in: only [run_tree] offers the spawn_agent tool. Pass a
Containment and the tree runs under it.
use ;
# async
Containment is inherit-and-narrow
The 0.4 policy becomes the boundary for spawned agents. Where Policy::merge
lets an overlay widen a base (allows union), Policy::contain derives a
child policy that can only narrow:
- denies union downward — a child adds restrictions;
- allows intersect downward — a child can never read, write, or execute anything its parent could not;
- the rule holds at any depth — no descendant can hold an effective allow the root did not grant.
let child_effective = parent_policy.contain; // child cannot widen
One spend ceiling above the task contract
The whole tree draws its token spend from one shared ledger. A spawned
TaskContract can set a tighter budget but never a looser one than the tree has
left; when the aggregate max_total_tokens is reached the tree halts as a whole.
A spawn that would breach any cap — agents, depth, or budget — is refused as a
tool result the parent can adapt to, and every spawn, refusal, and budget draw is
in the rusqlite trace as one reconstructable graph.
Run it live: cargo run --example subagents.
Part of initorigin
IO Harness is one of the initorigin products:
| Repo | What it is |
|---|---|
| io-harness | The Rust agent harness (the center product) |
| io-eval | Benchmark harness for io-harness |
| io-cli | Terminal app on io-harness |
| io-studio | Desktop coding studio on io-harness |
| website | Marketing site, docs, and blog |
Contributing
Read CONTRIBUTING.md. Work branches from develop, lands via
PR, and every user-facing change updates CHANGELOG.md. Releases
follow docs/RELEASE_PROCESS.md.
Security
Report vulnerabilities per SECURITY.md.
License
Apache-2.0. Copyright 2026 Aakash Pawar (InitOrigin). See LICENSE and NOTICE.