`CODEX_TEST_REMOTE_ENV` will make `test_codex` start the executor
"remotely" (inside a docker container) turning any integration test into
remote test.
- Split the feature system into a new `codex-features` crate.
- Cut `codex-core` and workspace consumers over to the new config and
warning APIs.
Co-authored-by: Ahmed Ibrahim <219906144+aibrahim-oai@users.noreply.github.com>
Co-authored-by: Codex <noreply@openai.com>
Cleanup image semantics in code mode.
`view_image` now returns `{image_url:string, details?: string}`
`image()` now allows both string parameter and `{image_url:string,
details?: string}`
## Summary
This PR narrows original image detail handling to a single opt-in
feature:
- `image_detail_original` lets the model request `detail: "original"` on
supported models
- Omitting `detail` preserves the default resized behavior
The model only sees `detail: "original"` guidance when the active model
supports it:
- JS REPL instructions include the guidance and examples only on
supported models
- `view_image` only exposes a `detail` parameter when the feature and
model can use it
The image detail API is intentionally narrow and consistent across both
paths:
- `view_image.detail` supports only `"original"`; otherwise omit the
field
- `codex.emitImage(..., detail)` supports only `"original"`; otherwise
omit the field
- Unsupported explicit values fail clearly at the API boundary instead
of being silently reinterpreted
- Unsupported explicit `detail: "original"` requests fall back to normal
behavior when the feature is disabled or the model does not support
original detail
Addresses #13586
This doesn't affect our CI scripts. It was user-reported.
Summary
- add `wiremock::ResponseTemplate` and `body_string_contains` imports
behind `#[cfg(not(debug_assertions))]` in
`codex-rs/core/tests/suite/view_image.rs` so release builds only pull
the helpers they actually use
add `web_search_tool_type` on model_info that can be populated from
backend. will be used to filter which models can use `web_search` with
images and which cant.
added small unit test.
## Why
Enterprises can already constrain approvals, sandboxing, and web search
through `requirements.toml` and MDM, but feature flags were still only
configurable as managed defaults. That meant an enterprise could suggest
feature values, but it could not actually pin them.
This change closes that gap and makes enterprise feature requirements
behave like the other constrained settings. The effective feature set
now stays consistent with enterprise requirements during config load,
when config writes are validated, and when runtime code mutates feature
flags later in the session.
It also tightens the runtime API for managed features. `ManagedFeatures`
now follows the same constraint-oriented shape as `Constrained<T>`
instead of exposing panic-prone mutation helpers, and production code
can no longer construct it through an unconstrained `From<Features>`
path.
The PR also hardens the `compact_resume_fork` integration coverage on
Windows. After the feature-management changes,
`compact_resume_after_second_compaction_preserves_history` was
overflowing the libtest/Tokio thread stacks on Windows, so the test now
uses an explicit larger-stack harness as a pragmatic mitigation. That
may not be the ideal root-cause fix, and it merits a parallel
investigation into whether part of the async future chain should be
boxed to reduce stack pressure instead.
## What Changed
Enterprises can now pin feature values in `requirements.toml` with the
requirements-side `features` table:
```toml
[features]
personality = true
unified_exec = false
```
Only canonical feature keys are allowed in the requirements `features`
table; omitted keys remain unconstrained.
- Added a requirements-side pinned feature map to
`ConfigRequirementsToml`, threaded it through source-preserving
requirements merge and normalization in `codex-config`, and made the
TOML surface use `[features]` (while still accepting legacy
`[feature_requirements]` for compatibility).
- Exposed `featureRequirements` from `configRequirements/read`,
regenerated the JSON/TypeScript schema artifacts, and updated the
app-server README.
- Wrapped the effective feature set in `ManagedFeatures`, backed by
`ConstrainedWithSource<Features>`, and changed its API to mirror
`Constrained<T>`: `can_set(...)`, `set(...) -> ConstraintResult<()>`,
and result-returning `enable` / `disable` / `set_enabled` helpers.
- Removed the legacy-usage and bulk-map passthroughs from
`ManagedFeatures`; callers that need those behaviors now mutate a plain
`Features` value and reapply it through `set(...)`, so the constrained
wrapper remains the enforcement boundary.
- Removed the production loophole for constructing unconstrained
`ManagedFeatures`. Non-test code now creates it through the configured
feature-loading path, and `impl From<Features> for ManagedFeatures` is
restricted to `#[cfg(test)]`.
- Rejected legacy feature aliases in enterprise feature requirements,
and return a load error when a pinned combination cannot survive
dependency normalization.
- Validated config writes against enterprise feature requirements before
persisting changes, including explicit conflicting writes and
profile-specific feature states that normalize into invalid
combinations.
- Updated runtime and TUI feature-toggle paths to use the constrained
setter API and to persist or apply the effective post-constraint value
rather than the requested value.
- Updated the `core_test_support` Bazel target to include the bundled
core model-catalog fixtures in its runtime data, so helper code that
resolves `core/models.json` through runfiles works in remote Bazel test
environments.
- Renamed the core config test coverage to emphasize that effective
feature values are normalized at runtime, while conflicting persisted
config writes are rejected.
- Ran `compact_resume_after_second_compaction_preserves_history` inside
an explicit 8 MiB test thread and Tokio runtime worker stack, following
the existing larger-stack integration-test pattern, to keep the Windows
`compact_resume_fork` test slice from aborting while a parallel
investigation continues into whether some of the underlying async
futures should be boxed.
## Verification
- `cargo test -p codex-config`
- `cargo test -p codex-core feature_requirements_ -- --nocapture`
- `cargo test -p codex-core
load_requirements_toml_produces_expected_constraints -- --nocapture`
- `cargo test -p codex-core
compact_resume_after_second_compaction_preserves_history -- --nocapture`
- `cargo test -p codex-core compact_resume_fork -- --nocapture`
- Re-ran the built `codex-core` `tests/all` binary with
`RUST_MIN_STACK=262144` for
`compact_resume_after_second_compaction_preserves_history` to confirm
the explicit-stack harness fixes the deterministic low-stack repro.
- `cargo test -p codex-core`
- This still fails locally in unrelated integration areas that expect
the `codex` / `test_stdio_server` binaries or hit existing `search_tool`
wiremock mismatches.
## Docs
`developers.openai.com/codex` should document the requirements-side
`[features]` table for enterprise and MDM-managed configuration,
including that it only accepts canonical feature keys and that
conflicting config writes are rejected.
## Summary
Instead of always adding inner function call outputs to the model
context, let js code decide which ones to return.
- Stop auto-hoisting nested tool outputs from `codex.tool(...)` into the
outer `js_repl` function output.
- Keep `codex.tool(...)` return values unchanged as structured JS
objects.
- Add `codex.emitImage(...)` as the explicit path for attaching an image
to the outer `js_repl` function output.
- Support emitting from a direct image URL, a single `input_image` item,
an explicit `{ bytes, mimeType }` object, or a raw tool response object
containing exactly one image.
- Preserve existing `view_image` original-resolution behavior when JS
emits the raw `view_image` tool result.
- Suppress the special `ViewImageToolCall` event for `js_repl`-sourced
`view_image` calls so nested inspection stays side-effect free until JS
explicitly emits.
- Update the `js_repl` docs and generated project instructions with both
recommended patterns:
- `await codex.emitImage(codex.tool("view_image", { path }))`
- `await codex.emitImage({ bytes: await page.screenshot({ type: "jpeg",
quality: 85 }), mimeType: "image/jpeg" })`
#### [git stack](https://github.com/magus/git-stack-cli)
- ✅ `1` https://github.com/openai/codex/pull/13050
- 👉 `2` https://github.com/openai/codex/pull/13331
- ⏳ `3` https://github.com/openai/codex/pull/13049
## Summary
Add original-resolution support for `view_image` behind the
under-development `view_image_original_resolution` feature flag.
When the flag is enabled and the target model is `gpt-5.3-codex` or
newer, `view_image` now preserves original PNG/JPEG/WebP bytes and sends
`detail: "original"` to the Responses API instead of using the legacy
resize/compress path.
## What changed
- Added `view_image_original_resolution` as an under-development feature
flag.
- Added `ImageDetail` to the protocol models and support for serializing
`detail: "original"` on tool-returned images.
- Added `PromptImageMode::Original` to `codex-utils-image`.
- Preserves original PNG/JPEG/WebP bytes.
- Keeps legacy behavior for the resize path.
- Updated `view_image` to:
- use the shared `local_image_content_items_with_label_number(...)`
helper in both code paths
- select original-resolution mode only when:
- the feature flag is enabled, and
- the model slug parses as `gpt-5.3-codex` or newer
- Kept local user image attachments on the existing resize path; this
change is specific to `view_image`.
- Updated history/image accounting so only `detail: "original"` images
use the docs-based GPT-5 image cost calculation; legacy images still use
the old fixed estimate.
- Added JS REPL guidance, gated on the same feature flag, to prefer JPEG
at 85% quality unless lossless is required, while still allowing other
formats when explicitly requested.
- Updated tests and helper code that construct
`FunctionCallOutputContentItem::InputImage` to carry the new `detail`
field.
## Behavior
### Feature off
- `view_image` keeps the existing resize/re-encode behavior.
- History estimation keeps the existing fixed-cost heuristic.
### Feature on + `gpt-5.3-codex+`
- `view_image` sends original-resolution images with `detail:
"original"`.
- PNG/JPEG/WebP source bytes are preserved when possible.
- History estimation uses the GPT-5 docs-based image-cost calculation
for those `detail: "original"` images.
#### [git stack](https://github.com/magus/git-stack-cli)
- 👉 `1` https://github.com/openai/codex/pull/13050
- ⏳ `2` https://github.com/openai/codex/pull/13331
- ⏳ `3` https://github.com/openai/codex/pull/13049
- add a local Fast mode setting in codex-core (similar to how model id
is currently stored on disk locally)
- send `service_tier=priority` on requests when Fast is enabled
- add `/fast` in the TUI and persist it locally
- feature flag
- replace show_nux with structured availability_nux model metadata
- expose availability NUX data through the app-server model API
- update shared fixtures and tests for the new field
## Summary
This changes `custom_tool_call_output` to use the same output payload
shape as `function_call_output`, so freeform tools can return either
plain text or structured content items.
The main goal is to let `js_repl` return image content from nested
`view_image` calls in its own `custom_tool_call_output`, instead of
relying on a separate injected message.
## What changed
- Changed `custom_tool_call_output.output` from `string` to
`FunctionCallOutputPayload`
- Updated freeform tool plumbing to preserve structured output bodies
- Updated `js_repl` to aggregate nested tool content items and attach
them to the outer `js_repl` result
- Removed the old `js_repl` special case that injected `view_image`
results as a separate pending user image message
- Updated normalization/history/truncation paths to handle multimodal
`custom_tool_call_output`
- Regenerated app-server protocol schema artifacts
## Behavior
Direct `view_image` calls still return a `function_call_output` with
image content.
When `view_image` is called inside `js_repl`, the outer `js_repl`
`custom_tool_call_output` now carries:
- an `input_text` item if the JS produced text output
- one or more `input_image` items from nested tool results
So the nested image result now stays inside the `js_repl` tool output
instead of being injected as a separate message.
## Compatibility
This is intended to be backward-compatible for resumed conversations.
Older histories that stored `custom_tool_call_output.output` as a plain
string still deserialize correctly, and older histories that used the
previous injected-image-message flow also continue to resume.
Added regression coverage for resuming a pre-change rollout containing:
- string-valued `custom_tool_call_output`
- legacy injected image message history
#### [git stack](https://github.com/magus/git-stack-cli)
- 👉 `1` https://github.com/openai/codex/pull/12948
Summary is a required parameter on UserTurn. Ideally we'd like the core
to decide the appropriate summary level.
Make the summary optional and don't send it when not needed.
## Summary
- make `Config.model_reasoning_summary` optional so unset means use
model default
- resolve the optional config value to a concrete summary when building
`TurnContext`
- add protocol support for `default_reasoning_summary` in model metadata
## Validation
- `cargo test -p codex-core --lib client::tests -- --nocapture`
---------
Co-authored-by: Codex <noreply@openai.com>
## Summary
Remove js_repl/node test-skip paths and make Node setup explicit in CI
so js_repl tests always run instead of silently skipping.
## Why
We had multiple “expediency” skip paths that let js_repl tests pass
without actually exercising Node-backed behavior. This reduced CI signal
and hid runtime/environment regressions.
## What changed
### CI
- Added Node setup using `codex-rs/node-version.txt` in:
- `.github/workflows/rust-ci.yml`
- `.github/workflows/bazel.yml`
- Added a Unix PATH copy step in Bazel workflow to expose the setup-node
binary in common paths.
### js_repl test harness
- Added explicit js_repl sandbox test configuration helpers in:
- `codex-rs/core/src/tools/js_repl/mod.rs`
- `codex-rs/core/src/tools/handlers/js_repl.rs`
- Added Linux arg0 dispatch glue for js_repl tests so sandbox subprocess
entrypoint behavior is correct under Linux test execution.
### Removed skip behavior
- Deleted runtime guard function and early-return skips in js_repl tests
(`can_run_js_repl_runtime_tests` and related per-test short-circuits).
- Removed view_image integration test skip behavior:
- dropped `skip_if_no_network!(Ok(()))`
- removed “skip on Node missing/too old” branch after js_repl output
inspection.
## Impact
- js_repl/node tests now consistently execute and fail loudly when the
environment is not correctly provisioned.
- CI has stronger signal for js_repl regressions instead of false green
from conditional skips.
## Testing
- `cargo test -p codex-core` (locally) to validate js_repl
unit/integration behavior with skips removed.
- CI expected to surface any remaining environment/runtime gaps directly
(rather than masking them).
#### [git stack](https://github.com/magus/git-stack-cli)
- ✅ `1` https://github.com/openai/codex/pull/12300
- ✅ `2` https://github.com/openai/codex/pull/12275
- ✅ `3` https://github.com/openai/codex/pull/12205
- ✅ `4` https://github.com/openai/codex/pull/12407
- ✅ `5` https://github.com/openai/codex/pull/12372
- 👉 `6` https://github.com/openai/codex/pull/12185
- ⏳ `7` https://github.com/openai/codex/pull/10673
## Summary
- Fix `js_repl` so `await codex.tool("view_image", { path })` actually
attaches the image to the active turn when called from inside the JS
REPL.
- Restore the behavior expected by the existing `js_repl`
image-attachment test.
- This is a follow-up to
[#12553](https://github.com/openai/codex/pull/12553), which changed
`view_image` to return structured image content.
## Root Cause
- [#12553](https://github.com/openai/codex/pull/12553) changed
`view_image` from directly injecting a pending user image message to
returning structured `function_call_output` content items.
- The nested tool-call bridge inside `js_repl` serialized that tool
response back to the JS runtime, but it did not mirror returned image
content into the active turn.
- As a result, `view_image` appeared to succeed inside `js_repl`, but no
`input_image` was actually attached for the outer turn.
## What Changed
- Updated the nested tool-call path in `js_repl` to inspect function
tool responses for structured content items.
- When a nested tool response includes `input_image` content, `js_repl`
now injects a corresponding user `Message` into the active turn before
returning the raw tool result back to the JS runtime.
- Kept the normal JSON result flow intact, so `codex.tool(...)` still
returns the original tool output object to JavaScript.
## Why
- `js_repl` documentation and tests already assume that `view_image` can
be used from inside the REPL to attach generated images to the model.
- Without this fix, the nested call path silently dropped that
attachment behavior.
## Why
`codex-rs/core/src/lib.rs` re-exported a broad set of types and modules
from `codex-protocol` and `codex-shell-command`. That made it easy for
workspace crates to import those APIs through `codex-core`, which in
turn hides dependency edges and makes it harder to reduce compile-time
coupling over time.
This change removes those public re-exports so call sites must import
from the source crates directly. Even when a crate still depends on
`codex-core` today, this makes dependency boundaries explicit and
unblocks future work to drop `codex-core` dependencies where possible.
## What Changed
- Removed public re-exports from `codex-rs/core/src/lib.rs` for:
- `codex_protocol::protocol` and related protocol/model types (including
`InitialHistory`)
- `codex_protocol::config_types` (`protocol_config_types`)
- `codex_shell_command::{bash, is_dangerous_command, is_safe_command,
parse_command, powershell}`
- Migrated workspace Rust call sites to import directly from:
- `codex_protocol::protocol`
- `codex_protocol::config_types`
- `codex_protocol::models`
- `codex_shell_command`
- Added explicit `Cargo.toml` dependencies (`codex-protocol` /
`codex-shell-command`) in crates that now import those crates directly.
- Kept `codex-core` internal modules compiling by using `pub(crate)`
aliases in `core/src/lib.rs` (internal-only, not part of the public
API).
- Updated the two utility crates that can already drop a `codex-core`
dependency edge entirely:
- `codex-utils-approval-presets`
- `codex-utils-cli`
## Verification
- `cargo test -p codex-utils-approval-presets`
- `cargo test -p codex-utils-cli`
- `cargo check --workspace --all-targets`
- `just clippy`
rm `remote_models` feature flag.
We see issues like #11527 when a user has `remote_models` disabled, as
we always use the default fallback `ModelInfo`. This causes issues with
model performance.
Builds on #11690, which helps by warning the user when they are using
the default fallback. This PR will make that happen much less frequently
as an accidental consequence of disabling `remote_models`.
### What
It's currently unclear when the harness falls back to the default,
generic `ModelInfo`. This happens when the `remote_models` feature is
disabled or the model is truly unknown, and can lead to bad performance
and issues in the harness.
Add a user-facing warning when this happens so they are aware when their
setup is broken.
### Tests
Added tests, tested locally.
## Summary
This PR adds host-integrated helper APIs for `js_repl` and updates model
guidance so the agent can use them reliably.
### What’s included
- Add `codex.tool(name, args?)` in the JS kernel so `js_repl` can call
normal Codex tools.
- Keep persistent JS state and scratch-path helpers available:
- `codex.state`
- `codex.tmpDir`
- Wire `js_repl` tool calls through the standard tool router path.
- Add/align `js_repl` execution completion/end event behavior with
existing tool logging patterns.
- Update dynamic prompt injection (`project_doc`) to document:
- how to call `codex.tool(...)`
- raw output behavior
- image flow via `view_image` (`codex.tmpDir` +
`codex.tool("view_image", ...)`)
- stdio safety guidance (`console.log` / `codex.tool`, avoid direct
`process.std*`)
## Why
- Standardize JS-side tool usage on `codex.tool(...)`
- Make `js_repl` behavior more consistent with existing tool execution
and event/logging patterns.
- Give the model enough runtime guidance to use `js_repl` safely and
effectively.
## Testing
- Added/updated unit and runtime tests for:
- `codex.tool` calls from `js_repl` (including shell/MCP paths)
- image handoff flow via `view_image`
- prompt-injection text for `js_repl` guidance
- execution/end event behavior and related regression coverage
#### [git stack](https://github.com/magus/git-stack-cli)
- ✅ `1` https://github.com/openai/codex/pull/10674
- 👉 `2` https://github.com/openai/codex/pull/10672
- ⏳ `3` https://github.com/openai/codex/pull/10671
- ⏳ `4` https://github.com/openai/codex/pull/10673
- ⏳ `5` https://github.com/openai/codex/pull/10670
Summary
- add a `prefer_websockets` field to `ModelInfo`, defaulting to `false`
in all fixtures and constructors
- wire the new flag into websocket selection so models that opt in
always use websocket transport even when the feature gate is off
Testing
- Not run (not requested)
- Keep `view_image` in the advertised tool list for all models.
- Return a clear error when the current model does not support image
inputs, and cover it with a unit test.
## Summary
Support updating Personality mid-Thread via UserTurn/OverwriteTurn. This
is explicitly unused by the clients so far, to simplify PRs - app-server
and tui implementations will be follow-ups.
## Testing
- [x] added integration tests
Agent wouldn't "see" attached images and would instead try to use the
view_file tool:
<img width="1516" height="504" alt="image"
src="https://github.com/user-attachments/assets/68a705bb-f962-4fc1-9087-e932a6859b12"
/>
In this PR, we wrap image content items in XML tags with the name of
each image (now just a numbered name like `[Image #1]`), so that the
model can understand inline image references (based on name). We also
put the image content items above the user message which the model seems
to prefer (maybe it's more used to definitions being before references).
We also tweak the view_file tool description which seemed to help a bit
Results on a simple eval set of images:
Before
<img width="980" height="310" alt="image"
src="https://github.com/user-attachments/assets/ba838651-2565-4684-a12e-81a36641bf86"
/>
After
<img width="918" height="322" alt="image"
src="https://github.com/user-attachments/assets/10a81951-7ee6-415e-a27e-e7a3fd0aee6f"
/>
```json
[
{
"id": "single_describe",
"prompt": "Describe the attached image in one sentence.",
"images": ["image_a.png"]
},
{
"id": "single_color",
"prompt": "What is the dominant color in the image? Answer with a single color word.",
"images": ["image_b.png"]
},
{
"id": "orientation_check",
"prompt": "Is the image portrait or landscape? Answer in one sentence.",
"images": ["image_c.png"]
},
{
"id": "detail_request",
"prompt": "Look closely at the image and call out any small details you notice.",
"images": ["image_d.png"]
},
{
"id": "two_images_compare",
"prompt": "I attached two images. Are they the same or different? Briefly explain.",
"images": ["image_a.png", "image_b.png"]
},
{
"id": "two_images_captions",
"prompt": "Provide a short caption for each image (Image 1, Image 2).",
"images": ["image_c.png", "image_d.png"]
},
{
"id": "multi_image_rank",
"prompt": "Rank the attached images from most colorful to least colorful.",
"images": ["image_a.png", "image_b.png", "image_c.png"]
},
{
"id": "multi_image_choice",
"prompt": "Which image looks more vibrant? Answer with 'Image 1' or 'Image 2'.",
"images": ["image_b.png", "image_d.png"]
}
]
```
This seems to be necessary to get the Bazel builds on ARM Linux to go
green on https://github.com/openai/codex/pull/8875.
I don't feel great about timeout-whack-a-mole, but we're still learning
here...
If an image can't be read by the API, it will poison the entire history,
preventing any new turn on the conversation.
This detect such cases and replace the image by a placeholder
## Summary
- add `TestCodex::submit_turn_with_policies` and extend the response
helpers with reusable tool-call utilities
- update the grep_files, read_file, list_dir, shell_serialization, and
tools suites to rely on the shared helpers instead of local copies
- make the list_dir helper return `anyhow::Result` so clippy no longer
warns about `expect`
## Testing
- `just fix -p codex-core`
- `cargo test -p codex-core --test all
suite::grep_files::grep_files_tool_collects_matches`
- `cargo test -p codex-core
suite::grep_files::grep_files_tool_collects_matches -- --ignored`
(filter requests ignored tests so nothing runs, but the build stays
clean)
------
[Codex
Task](https://chatgpt.com/codex/tasks/task_i_69112d53abac83219813cab4d7cb6446)
solves: https://github.com/openai/codex/issues/5675
Block non-image uploads in the view_image workflow. We now confirm the
file’s MIME is image/* before building the data URL; otherwise we emit a
“unsupported MIME type” error to the model. This stops the agent from
sending application/json blobs that the Responses API rejects with 400s.
<img width="409" height="556" alt="Screenshot 2025-10-28 at 1 15 10 PM"
src="https://github.com/user-attachments/assets/a92199e8-2769-4b1d-8e33-92d9238c90fe"
/>
Adds a new ItemStarted event and delivers UserMessage as the first item
type (more to come).
Renames `InputItem` to `UserInput` considering we're using the `Item`
suffix for actual items.
## Summary
- add a reusable `ev_response_created` helper that builds
`response.created` SSE events for integration tests
- update the exec and core integration suites to use the new helper
instead of repeating manual JSON literals
- keep the streaming fixtures consistent by relying on the shared helper
in every touched test
## Testing
- `just fmt`
------
https://chatgpt.com/codex/tasks/task_i_68e1fe885bb883208aafffb94218da61
## Summary
- replace manual event polling loops in several core test suites with
the shared wait_for_event helpers
- keep prior assertions intact by using closure captures for stateful
expectations, including plan updates, patch lifecycles, and review flow
checks
- rely on wait_for_event_with_timeout where longer waits are required,
simplifying timeout handling
## Testing
- just fmt
------
https://chatgpt.com/codex/tasks/task_i_68e1d58582d483208febadc5f90dd95e
# Tool System Refactor
- Centralizes tool definitions and execution in `core/src/tools/*`:
specs (`spec.rs`), handlers (`handlers/*`), router (`router.rs`),
registry/dispatch (`registry.rs`), and shared context (`context.rs`).
One registry now builds the model-visible tool list and binds handlers.
- Router converts model responses to tool calls; Registry dispatches
with consistent telemetry via `codex-rs/otel` and unified error
handling. Function, Local Shell, MCP, and experimental `unified_exec`
all flow through this path; legacy shell aliases still work.
- Rationale: reduce per‑tool boilerplate, keep spec/handler in sync, and
make adding tools predictable and testable.
Example: `read_file`
- Spec: `core/src/tools/spec.rs` (see `create_read_file_tool`,
registered by `build_specs`).
- Handler: `core/src/tools/handlers/read_file.rs` (absolute `file_path`,
1‑indexed `offset`, `limit`, `L#: ` prefixes, safe truncation).
- E2E test: `core/tests/suite/read_file.rs` validates the tool returns
the requested lines.
## Next steps:
- Decompose `handle_container_exec_with_params`
- Add parallel tool calls
pakrym-oai ·
Ahmed Ibrahim ·
Anton Panasenko ·
Curtis 'Fjord' Hawthorne ·
Eric Traut ·
sayan-oai ·
Michael Bolin ·
pash-openai ·
jif-oai ·
Dylan Hurd ·
charley-oai ·
zhao-oai ·