* fix(agents): drop empty strings from rebuilt user content
* fix(agents): normalize empty content before sanitizer early returns
* docs(agents): clarify input sanitization provider limits
* fix(middleware): scan PII emails in linear time
The email detector's pattern restarts at every position inside a
whitespace-free run and consumes the rest of the run before failing to
find '@', so a scan is quadratic in the run length. PiiRedactionMiddleware
re-redacts every user message on every model call, on the event loop, so
one pasted 100 KB hex dump stalled the Gateway for ~6 s per model call.
Scan from run starts only (a local part must reach the end of its run),
and match anchored where the previous match ended so glued addresses
such as 'a@b.cc+c@d.org' keep both matches, exactly as before.
* docs(changelog): reference #8006 for the linear PII email scan
* fix(middleware): group the embedded email pattern and pin every detector's linearity
Wrap the pattern behind the run-start lookbehind in a group so a future
top-level alternative in _EMAIL_PATTERN cannot escape the lookbehind, and
add one whitespace-free payload per other detector to the linearity test
so the AGENTS.md rule is enforced for all of them.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* refactor(agent): ground runtime decisions in structured evidence
Use producer status and structured errors for tool recovery, preserve memory context without lexical confirmation, and remove predetermined receipt and skill conclusions.
Require explicit MCP discovery and authenticated schedule trial actions. Preserve authorization, ownership, isolation, and bounded execution; update documentation and regression coverage.
* test(sandbox): expect read_file initialization error callback
* fix(agent): address evidence review follow-ups
* fix(agent): preserve retry budgets for OpenAI transport errors
* fix(agent): expose tool execution status in model requests
Project validated execution metadata and exact tool text into request-only JSON so status survives provider serialization. Preserve stored results and receipt hashes, cover SDK and graph boundaries, and migrate replay input hashes without changing recorded responses.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(agents): keep HarnessGuard from rewriting the result that ends a loop
The alternating-loop check fired when three of the last four tool calls
failed, without checking the current call. After A and B failed in turn,
a successful B therefore received the OSCILLATION DETECTED warning: the
model was told to stop just as the loop ended, and structured output such
as JSON was corrupted by the appended text.
Only a failing call now continues the pattern, so successful results reach
the model unchanged. Failing alternation still warns.
* fix(agents): only warn on an alternating loop when the whole window failed
The oscillation check still counted 3 errors out of the last 4 calls, so a
window that contained a success could warn on the next failure, e.g.
A err, B err, A ok, B err. A success ends the loop, so require all four
calls in the window to have failed, and pin the break shapes with tests.
---------
Co-authored-by: Totoro <msy626836554@gmail.com>
* fix(agents): keep todo reminders in Goal turns after an earlier provider stop
TodoMiddleware skipped completion reminders whenever runtime.context held
safety_capped or model_length_capped. The worker keeps that key across the
run's hidden Goal continuation turns so the run record reports the first
cap, and an unmet Goal continues after these provider stops (it stands down
only on loop and token caps). After one capped response, every continuation
turn therefore lost its todo reminders and could stop with unfinished items.
Loop and token stops stay run-level and are still read from the context.
Provider safety and length stops now apply to the response they ended,
identified by the safety_termination / model_length_termination marker that
those guards stamp on it. The check still runs before the parent hook, so a
capped response cannot be resumed by the parallel-write retry.
* refactor(agents): import provider-stop markers from the guards that stamp them
TodoMiddleware matched the safety and length markers by string literals that
duplicated the guards' own. Each guard now exports its marker and stop reason
as module constants, used at its stamp and check sites and imported by
TodoMiddleware, so a rename in a guard cannot silently disable suppression.
Comment that completion_reminder_hard_stop_reasons is the inventory surface
and only its run-level entries are read from runtime.context, and run the
worker-level Goal continuation test for the safety guard too, which
overwrites stop_reason instead of keeping the first one.
---------
Co-authored-by: Totoro <msy626836554@gmail.com>
* fix(memory): skip text-less turns when formatting the memory prompt
A content-less message rendered as the literal "None", and a block list
without text blocks rendered as its Python repr, including any base64
data URL. Normalize through the same rules as the sibling content-to-text
helpers and skip turns that carry no text.
* test(memory): cover whitespace-only assistant turns
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(agent): stop todo reminders after run hard limits
Respect loop_capped and token_capped before scheduling completion reminders, and include the behavior in the assembly policy fingerprint.
Cover sync and async agent graphs, blocked post-stop tools, preserved Todo state, and continuation from the same thread checkpoint. Validation: 316 targeted tests passed.
* docs(agent): explain todo behavior after hard stops
Document that loop and token hard stops suppress Todo completion reminders while retaining unfinished tasks for later runs.
* docs(changelog): record todo hard-stop fix
Add English and Chinese Unreleased entries referencing issue #7953.
* fix(agent): mark safety stops with partial responses
* fix(agent): honor provider stops before todo retries
* docs(agent): clarify todo behavior after provider stops
* test(agent): isolate todo safety-chain runtime dependencies
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Totoro <msy626836554@gmail.com>
* fix(memory): restore facts from older backups
Use the current snapshot revision for existing facts during backup import so saved contents can be restored after later edits. Preserve manifest and fact preconditions, scope isolation, and caller-owned input data.
* refactor(memory): share import revision preconditions
* docs(memory): fit import guidance within chain budget
* fix(memory): validate backup revisions before restoration
---------
Co-authored-by: liyinlong <173714821+lilong555@users.noreply.github.com>
Tool-call ids are unique per assistant response, not per conversation.
extract_skills built a single id -> path map over the whole message
list, so a later read that reused an id overwrote the earlier one: the
earlier skill silently dropped out of the ledger and its correct
ToolMessage logged "mismatched skill read metadata".
Rebuild the map from each AIMessage's own calls and resolve a
ToolMessage against the nearest preceding response, matching the
pairing rule tool_call_args.pair_tool_call_results already applies.
Fixes#7858
Signed-off-by: Batianxieshen1 <280706568+Batianxieshen1@users.noreply.github.com>
Co-authored-by: Batianxieshen1 <280706568+Batianxieshen1@users.noreply.github.com>
* feat(subagents): continue native batches and honor item dependencies
* docs: link native batch follow-up changelog entries
* test(migrations): pin isolated history-seed upgrade to 0050
* fix(subagents): preserve follow-up scope, blockers and fair scheduling
* test(memory): freeze capacity evaluation time
* fix(subagents): guard follow-up admission and retain run controls
* fix(subagents): enforce runs:cancel on tool cancellation of follow-up batches
* style(tests): format test_batch_followup_host with ruff
* fix(subagents): drop the admission checkpoint check and keep SDK cancel compatible
The checkpoint check inside run admission waited on the checkpoint saver's
lock while holding the SQLite write lock, which could make another chat's
checkpoint write fail. Remove it; dispatch still checks the conversation
before admission.
A follow-up waiting for an unanswered question now keeps its claim until the
lease expires instead of rereading the conversation every poll. Cancel passes
the caller's run authority only to submitters that take it, so existing SDK
submitters keep the two-argument call. Document that retrying a prerequisite
by hand does not requeue its blocked items, and list 0052 as the migration head.
---------
Co-authored-by: Totoro-qaq <279883115+Totoro-qaq@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(agents): pair null call IDs with empty result IDs
* fix(agents): treat producer sentinel IDs as absent when pairing
Middleware producers spell a missing provider ID three ways: "" is canonical,
str(tool_call.get("id", "")) yields "None" once the key is present with a
null value, and the artifact/deferred/knowledge middlewares fall back to
"missing_tool_call_id". Only "" reached the pairing pass, so a result carrying
either sentinel was dropped as an orphan and the middleware's guidance was
replaced by the interrupted placeholder — the exact outcome this PR set out to
avoid, just through a different spelling.
Route every absent spelling through one canonicalisation used by the pairing
gate, the candidate comparison and the turn-completeness count.
---------
Co-authored-by: huyengiang101086-spec <270684046+huyengiang101086-spec@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
extract_message_text falls back to str(content), so a message whose content is None becomes the truthy literal 'None'. That string then reaches signal detection and the memory-update prompt as if the user had written it. The canonical helper (utils/messages.py:message_content_to_text) and the mem0 copy both return '' for this shape and the canonical one documents exactly this failure mode.
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(todos): keep an unusable stored todo list from failing every model call
`todos` is a reducer channel that `POST /threads/{id}/state` and run input can
Overwrite directly, but neither boundary validated its shape. The todo
middleware rendered it with `entry.get(...)` in both `before_model` and
`after_model`, so a non-object entry — or a value that is not a list — raised
AttributeError on every model call, permanently for that thread.
Validate caller-written todos beside `goal` in `_normalize_external_todos`: a
list of objects with string content and a known status, or HTTP 400. The
middleware now reads the channel through `_usable_todos` and ignores entries of
any other stored shape, so checkpoints and direct integrations written before
this boundary still run.
* fix(todos): normalize stored todos in token-usage attribution
TokenUsageMiddleware reads the same stored `todos` channel through
`_build_attribution` whenever the last AIMessage calls write_todos, and
`token_usage.enabled` defaults on, so a value the todo middleware now tolerates
still aborted the step here. Route the stored list through `_normalize_todos`
before reading entries.
Document that a caller-written todo without a status is accepted as pending and
cover that shape at both external boundaries.
* docs: keep backend agent guidance within size budgets
* fix(todos): keep the channel metadata strip on caller-written todos
The dedicated todos branch in strip_server_owned_state_metadata replaced the
generic list branch, which stripped server-owned metadata from every entry. A
caller could therefore persist additional_kwargs.original_user_content,
untrusted_input, or artifact.knowledge_sources on a todo entry. Re-apply the
per-entry strip after normalization, keeping None and empty lists untouched.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Context compaction runs from abefore_model/aafter_model on the shared loop,
and its async candidate loop constructed the summary provider inline.
create_chat_model can read local CLI credentials while it is constructed
(Codex auth.json, Claude Code credential files), so an automatic compaction
stalled every other request for that read.
Split construction out of _model_for and add _amodel_for, which builds the
provider on the assembly pool; the sync path keeps building inline. Anchor
and failure-cache semantics are unchanged, so a broken candidate still falls
through to the next one, and inference still awaits on the loop.
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Thread title generation runs inside the agent graph (aafter_model), and it
built its configured model inline. create_chat_model can read local CLI
credentials while it is constructed (Codex auth.json, Claude Code credential
files), so the first turn of every new thread read them on the shared loop
and other requests waited for it.
Build the provider through run_assembly, the dedicated assembly pool the
one-shot helpers, skill moderation, the goal evaluator and start_run already
use. Inference still awaits on the loop, and the sync path is unchanged.
A Blockbuster regression builds the real Codex provider: on main the gate
rejects the credential read, the broad fallback swallows it, and the local
fallback title replaces the model's title; with the change the provider is
constructed on a worker thread and the model's title is kept.
* feat(extension-api): add task identity fields to CompactionEvent (0.2.10)
CompactionEvent carried the transform, its hashes and its counts, but
nothing that names the task, run or thread the compaction happened in.
An observer that wants to relate a compaction to the run that produced it
had to match hashes across sessions, which is unreliable.
Append three optional fields, task_id, run_id and thread_id (str | None,
default None). Existing keyword and positional construction is unchanged,
so already-released extensions keep working. The host fills them in the
next commit.
Bump deerflow-extension-api to 0.2.10 and the harness's exact pin with it.
* fix(extensions): hand compaction observers the live task store and its identity
The summarization middleware already recovers the live task store from
the runtime to observe its summary system call, and the registry
allocates that store precisely because a compaction observer is
registered. notify_context_compacted() then discarded it and handed every
observer a detached store, with a docstring claiming there was no live
task.
- The lead run worker and the subagent executor now seed every task store
they allocate with the task's TaskInfo, not only when a lifecycle
contributor is registered; the lifecycle notification reuses the seeded
object. A subagent without a parent run_id still gets no TaskInfo.
- compact_state() and acompact_state() pass the store from
task_store_from_runtime() to _record_compaction().
- notify_context_compacted() takes an optional task_store. A live store
goes to the observers and fills the event's task_id/run_id/thread_id
from its TaskInfo; without one (manual /compact runs outside any run)
observers still receive a detached store and the ids stay None.
For a background subagent the store keeps its public scope id (the
provider tool_call_id) while TaskInfo.task_id stays the execution id, as
lifecycle contributors already see it; the event follows TaskInfo.
* docs(extensions): document compaction event identity and seeded TaskInfo
The extensions guide and the developer manual still said compaction
observers always receive a detached store because no task is live at the
call site. Describe what the host does now: lead runs and subagents with a
parent run seed every task store with TaskInfo, compaction observers get
the live store, and CompactionEvent's task_id/run_id/thread_id come from
it; only manual /compact falls back to a detached store with None ids.
Adds the 0.2.10 row to the contract version table (PR number pending).
* docs(changelog): note compaction observers receive the live task identity
* docs(extensions): list compaction observers among task-store triggers
* docs: reference #7831 for the compaction event identity change
* docs(extensions): backfill contract history rows 0.2.5 to 0.2.9
The version table jumped from 0.2.4 to 0.2.10 although 0.2.5-0.2.9
shipped. Add those rows, attributing names merged without a bump to
the first release that carried them (#5796 in 0.2.5, #6920 and #5645
in 0.2.8, #7729 in 0.2.10). The page intro now says it documents
0.2.4 plus the 0.2.10 CompactionEvent fields, and points to the
history for the rest.
* fix(middlewares): prevent todo retries after text-only output caps
* docs(middlewares): clarify text-only output cap markers
* test(subagents): isolate cleanup test from shared assembly pool
* docs(middlewares): keep cap guidance within chain budget
---------
Co-authored-by: linkangjun <331227811+linkangjun@users.noreply.github.com>
Loop detection, clarification and dangling-tool-call repair parse model-provided
tool arguments and options. A JSON string, Python structure or native option
label nested past the interpreter recursion limit raised RecursionError and
aborted the run; these paths now treat it like any other unusable payload
(opaque args, an empty replay object, or a skipped option), and the dict-option
flatten and _stable_tool_key use guarded serialization.
Rebased onto current main; the stale-base docs commit is superseded by main and
the AGENTS note is trimmed to stay inside the guidance chain budget.
* fix(runtime): charge a steered subagent's usage to the token budget
A task that finishes after a Steer reports through a receipt HumanMessage, so its usage never reached the dispatching AIMessage the token budget reads. Carry the usage over when the receipt is delivered.
* fix(runtime): report deferred usage with no AIMessage to charge
Log the rare case instead of dropping the usage silently, and scan for AIMessages once per delivery.
* fix(memory): tolerate unbounded stored fact confidence
A stored memory fact can carry a JSON integer such as 10**400. float() on it
raises OverflowError in _coerce_source_confidence and in the dedup merge
comparison, aborting the whole update cycle even though both sites already
handle every other unusable confidence. Treat the overflow like a missing or
non-finite value: 0.5 for ranking, 0.0 for the merge comparison.
* fix(memory): harden the remaining fact-confidence coercions
The import normalizer, prompt builder and relevance scorer each coerce a
stored fact confidence with float() and caught only TypeError/ValueError, so
an unbounded JSON integer such as 10**400 raised OverflowError: import failed
before the updater fallbacks ran, and prompt/relevance ranking could abort.
Catch OverflowError and take the existing defaults; document the full set of
coercions.
* fix(clarification): keep each question when a provider reuses a call ID
The clarification ToolMessage ID, which is also the human-input
request_id, was clarification:{tool_call_id}. Providers that number
calls per response reuse call_0 across turns, so a later question took
the earlier one's ID: add_messages replaced the earlier question in
place and left the new call without a result.
Add a digest of the issuing AIMessage ID. A retry of the same call comes
from the same AIMessage and keeps its ID; without that message in state
the ID keeps its previous form.
* docs(changelog): reference #7762 for the clarification call ID fix
* fix(agents): ignore malformed entries in a serialized MCP routing index
`McpRoutingMiddleware._normalize_index` documents that it accepts "arbitrary
serialized routing data, not only the output of the builder", but two shapes
escaped the coercion and raised instead:
- an entry that is not a mapping (`str`, `list`, `None`, a number) reached
`.get` and raised `AttributeError`;
- a non-finite `priority` raised `OverflowError` from `int()` — JSON accepts
`Infinity`/`-Infinity` literals, so a hand-edited or foreign index can carry
one.
The middleware is constructed per run, so either shape fails every model call
in that process instead of the entry being ignored the way an entry with no
keywords already is.
Both now degrade to "not indexable": a non-mapping entry is skipped, and a
priority that cannot be a finite int falls back to 0 (the existing value for
`None`/non-numeric priorities). Valid entries are unchanged.
Tests cover each rejected shape, the control shapes that already degraded, and
the builder-shaped output that must stay identical. Dropping only the mapping
guard fails the non-mapping cases; dropping only `OverflowError` fails the
non-finite cases.
* fix(mcp): handle infinite routing priorities in the builder
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat(runtime): add Queue and Steer for active Web runs
* style(frontend): format Queue and Steer controls
* fix(runtime): retain user Steer controls and order active inputs
* docs: add Chinese changelog entry for Queue and Steer
---------
Co-authored-by: Totoro-qaq <279883115+Totoro-qaq@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(runtime): present outputs before a loop wrap-up and explain step-limit stops
Loop-detection warnings now ask the agent to present the files it already
created in /mnt/user-data/outputs before its final answer, when
present_files is available.
A run that exhausts recursion_limit now ends with stop_reason
recursion_capped and a plain message that lists outputs it created but
did not present. An active goal stands down without an evaluator call.
The /wait error envelope keeps the GraphRecursionError name, and IM
channels reply with the step-limit message instead of a generic failure.
* docs(changelog): note run-end delivery and step-limit stops (#7588)
* test(runtime): stop pinning LangGraph's step count in the step-limit test
The produced paths and the message already follow the observed model
calls, so the exact count only pinned LangGraph's per-step accounting.
Also note on the step-limit goal branch that its caller passes no
evaluator factory, so it has to stay ahead of the evaluator section.
---------
Co-authored-by: Totoro-qaq <279883115+Totoro-qaq@users.noreply.github.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(memory): flush pre-compaction memory off the event loop
The async compaction path fired the before-summarization hooks inline.
memory_flush_hook hands the summarized messages to add_nowait, which is
sync HTTP for mem0 and Honcho (inherited default -> add) and OpenViking
(its own override), so every automatic compaction with an HTTP memory
backend blocked the Gateway event loop for the whole request.
acompact_state now runs the hooks through asyncio.to_thread, as
MemoryMiddleware.aafter_agent already does for its writes. Ordering,
failure isolation, summary-first timing and context propagation are
unchanged; the sync compact_state path is untouched.
* docs(changelog): reference #7530 for the pre-compaction memory flush fix
* test(memory): anchor the OpenViking pre-compaction flush off the event loop
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat(runtime): honor the web UI language in replies and DeerMem updates
Carry Settings > Appearance > Language as request-only run data: the
Gateway validates context.locale against a finite allowlist, the lead
agent prefers it for replies, and bundled DeerMem writes new facts and
summary prose in it. Explicit user language requests still take
precedence; checkpoint configurable, static prompts, and memory backend
APIs are unchanged.
Refs #7287
Co-Authored-By: Claude <noreply@anthropic.com>
* fix(runtime): guard language context and pin locale maps
* test(runtime): pin UI locales across frontend and Gateway
Add the shared locale fixture and document the intentional language fallback for internal runs. Clarify live-locale precedence in the run context contract.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* fix(sandbox): reject write_file payloads that are the elision placeholder
The tool-output budget middleware replaces a superseded write_file payload
with a deterministic placeholder in the model-bound request only. That
placeholder is text the model sees in its own history, so it can imitate it
and submit it back as real write_file content: #7319 reports a delivered
file that was 194 bytes of placeholder.
write_file now rejects a payload that is the placeholder (whole payload,
allowing only surrounding whitespace) with an actionable error telling the
model to read_file the target path and write the real content; nothing is
written. The match is whole-payload on purpose: a substring guard would
block legitimate edits to this repository, whose constants.py and
persistence docs quote the template verbatim.
The placeholder wording moves to one shared constant,
WRITE_ELISION_PLACEHOLDER_TEMPLATE in deerflow.constants, which the
middleware renders from and the guard matches on, so the two cannot drift.
Regression tests fail on base (7 failed, 6 passed) and pass with the fix;
near-miss payloads that merely quote the placeholder still write.
Refs #7319
* fix(sandbox): match complete write elision placeholders
* docs: clarify write placeholder validation scope
* chore: re-trigger CLA status check
* fix(sandbox): preflight async writes and trim guidance
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(memory): drop unusable numbers in stale extensions and consolidation confidence
* fix(memory): log defaulted consolidation confidence and pin the int passthrough
* fix(memory): rank capacity eviction per record, not per fact_id
select_facts_for_capacity keyed every score by fact_id, so an imported
batch that repeats an id collapsed into a single dict entry: the last
record's score won, and both the ranking pass and the evicted audit
read that one value for every position. A 0.9-confidence record could
therefore be evicted while its own 0.1-confidence duplicate survived.
The import path keeps caller-supplied ids without checking them for
uniqueness, and any over-cap import lands here.
Score by position instead: a parallel list next to the indexed facts,
so ranking and the audit read each record's own score. The public
``scores`` dict stays keyed by fact_id with last-write-wins
semantics, keeping the DeerMem benchmark contract and the callers
that never read it unchanged.
Red on main: test_confidence_policy_scores_duplicate_fact_ids_per_record
fails with the highest-confidence record evicted; green on this branch.
* fix(utils): keep share-less UNC roots out of the extended-length prefix
extended_length_path prefixed every absolute UNC path with
\\?\UNC\, but Win32 only accepts \\?\UNC\server\share\... — a
share-less root (\\server, \\server\, or a bare \) is not a valid
device path, so every Win32 call handed the prefixed spelling fails.
Only prefix when both the server and the share are present;
otherwise return the ordinary spelling unchanged.
Red on main: the \\server, \\server\, //, and //server cases of
test_windows_extended_spelling assert the forged prefix; green on
this branch.
* fix(subagents): report model_length_capped when a subagent hits the output limit
ModelLengthFinishReasonMiddleware only ran on the lead chain. A subagent
whose response was cut at the provider output limit (finish_reason=length,
stop_reason=max_tokens, MAX_TOKENS, Responses max_output_tokens) reached
the lead as a clean `completed`, and a tool call truncated at that
boundary still executed with partial arguments.
Register the same middleware on the subagent chain, in the lead's
relative position (after configured extensions, before Safety). It now
also records each detected cap per context run_id and exposes
`consume_stop_reason`, so the executor's existing duck-typed guard
collection reports `stop_reason=model_length_capped`. Add the value to
the subagent status contract (Python enum, contract fixture, frontend
whitelist) with the label "model output length limit", and update the
subagent docs.
Tests cover the middleware channel, chain placement, the contract, and
an end-to-end executor run with a fake model.
Co-Authored-By: Claude Code <noreply@anthropic.com>
* test(tasks): cover cap reasons on completed and failed runs
Extend the existing shared-contract round-trip matrix to preserve both terminal statuses alongside every supported stop reason, including model_length_capped and loop_capped.
---------
Co-authored-by: huangzz <110116@nd.com>
Co-authored-by: Claude Code <noreply@anthropic.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix(sandbox): treat a fetched process substitution as a program operand
`bash <(curl url)` hands the fetched file to bash as an *operand*, not as a
redirect: bash runs it. The audit only recognised the stdin spelling
(`bash < <(curl url)`), so the operand spelling executable-fetched content
through the sandbox audit unimpeded — the miss documented in the middlewares
AGENTS.md known-gaps list.
An interpreter in command position whose first operand is a risky process
substitution now blocks. The two exceptions mirror the stdin rule: a script
operand in front (`bash script.sh <(curl url)`) keeps the substitution an
ordinary argument, and a shell noexec flag (`bash -n <(curl url)`) only
parses it.
Verified in Git Bash:
bash <(echo "echo FETCHED_AS_PROGRAM") -> FETCHED_AS_PROGRAM
bash <(echo "echo FETCHED_WITH_ARG") consumer.sh -> FETCHED_WITH_ARG
bash -n <(echo "echo NOEXEC") -> exit 0, no output
* docs(sandbox): clarify substitution audit limitations
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
