Port from can1357/oh-my-pi#10521: their loop guard only hashed single-call
turns, so a model replaying the same multi-call batch every iteration was
never counted; they widened the hash to the whole batch. Hermes has the
same blind spot in a different shape: observe_call tracks a CONSECUTIVE
identical-call streak, so an A,B,A,B,... cycle of identical (args, result)
pairs resets the streak on every alternation and runs to the iteration
budget unflagged (live-reproduced: 60 calls in a 2-cycle, zero notices,
no hard stop).
Add a period-2..4 cycle detector over a bounded per-turn call history:
notice on the STALL_GUARD_IDENTICAL_CALL_THRESHOLD-th identical lap,
hard stop at no_progress_block_after laps under hard_stop_enabled — the
same thresholds the period-1 streak uses. Cycles whose results change
between laps never fire (real progress); cycles made only of poller-exempt
tools are exempt (legitimate waiting), matching single-call semantics.
Widen the streak-stop propagation seam in run_agent.py to carry the new
decision code.
- shell_hooks is the shared home: _ToolMatcherMixin (matcher compile + matches_tool),
_payload_fields, _forget_home_registrations, _home_key, _utc_now_iso now serve
outbound_webhooks too (copies deleted; every log string byte-identical).
- shell_hooks: response parsing is a per-event dispatch table; _spawn diagnostic
dict + _evaluate_result shared by the live callback and run_once;
_locked_update_approvals POSIX/non-POSIX bodies merged via ExitStack.
- tool_guardrails: ToolCallGuardrailConfig thresholds from a _THRESHOLD_SOURCES
table (nested-wins-over-flat preserved); _int_at_least replaces
_positive_int/_non_negative_int; observe_identical_call (0 refs) folded into
observe_call; _halt helper for hard-stop decisions.
- tool_dispatch_helpers: _plan_tool_batch_segments split into _batch_admission +
close/extend helpers with the post-hoc normalization merged in.
- Comment/docstring compaction keeping every stated rule.
Before turning hard stops on for unattended platforms, make sure they cannot
cut off normal work:
- Edit -> re-run is progress. A successful mutating call (write_file/patch,
a green terminal/execute_code, browser actions, job/message/cron/memory/
skill mutations) marks progress for every failing signature still being
counted this turn; the next identical retry restarts its streak instead
of accumulating toward exact_failure_block_after. A pure replay never
mutates anything between attempts, so it is still blocked at 5.
- Distinct red commands are diagnosis. For FAILURE_TOLERANT_TOOL_NAMES
(terminal, execute_code, process pollers, browser_navigate, web_extract)
same_tool_failure_halt_after warns but never halts.
- subagent and api_server keep the warn-only default: both are supervised
task loops with a live parent/client and do real edit -> re-run work.
Live A/B (real AIAgent platform=telegram, real patch+terminal, 8 rounds of
patch -> red check -> patch ...):
unmitigated branch: HALTED at round 6 (repeated_exact_failure_block)
this commit: COMPLETED all 8 rounds, final answer delivered
Loop shapes still stopped: identical failing read_file 8 calls,
identical successful terminal 5 calls (vs 602 on main).
Six new tests pin these flows; all fail on the unmitigated version.
Widen the salvaged #49189 hard-stop default so it covers the loop shape in
the #100849 debug bundle and #89069: a model replaying the same SUCCESSFUL
call (terminal, skill_view, memory) with a byte-identical result. The
per-turn idempotent_no_progress block only tracks IDEMPOTENT_TOOL_NAMES, so
those loops ran until the iteration budget (600 calls, ~40 min) with only a
notice appended.
- agent/tool_guardrails.py: observe_call's tool-agnostic consecutive-identical
streak raises a halt (identical_call_streak_halt) at
hard_stop_after.idempotent_no_progress when hard stops are active. Pollers
stay exempt; a changed result resets the streak; warning-only sessions are
unchanged.
- run_agent.py: surface that halt from _append_guardrail_observation like
every other guardrail halt (appends guidance, ends the turn).
- hermes_cli/config_defaults.py: declare non_interactive_hard_stop_enabled.
- docs: configuration.md describes the streak hard-stop.
- tests: streak halts terminal under hard_stop; never under soft mode,
for pollers, or when results change.
Live A/B (real AIAgent platform=telegram, mocked client replaying one call):
identical failing read_file main: 602 API calls, budget exhausted
branch: 8 calls, repeated_exact_failure_block
identical successful terminal main: 602 API calls, budget exhausted
branch: 5 calls, identical_call_streak_halt
Treat skill_view and skills_list as idempotent read-only tools so the existing no-progress guardrail can warn or block repeated identical skill loads. This prevents large skill outputs from being re-added to the context in tool loops.
Add regression coverage for repeated skill_view results under hard-stop guardrails.
Composio eval traces showed Hermes wasting turns re-issuing identical tool
calls (same tool, same args, same result — 3x/4x in one run) and ending
turns by announcing an action it never took. Two conservative, config-gated
guards (agent.stall_guards, default true):
- Identical-call loop breaker: ToolCallGuardrailController.observe_identical_call
tracks the consecutive streak of (tool, canonical args, result-hash); on
the 3rd identical call a compact one-line notice is appended to that tool
RESULT at construction time (cache-safe — tool results are append-only).
Never blocks the call. Pollers (process, *_get_result, *_poll) are exempt
via STALL_GUARD_REPEATABLE_TOOLS. Streak resets on any different call,
changed result, or new turn. Observed on the raw result before the
tool-loop warning suffix so its changing count can't defeat matching.
- Said-continue-but-stopped recovery: trailing_continue_intent() detects a
short reply ENDING on an announced next action ('Let me now…', 'I will
now…', 'Next, I…'); the conversation loop feeds it into the EXISTING
intent-ack continuation path (same interim-assistant + user-nudge
mechanism, same codex_ack_continuations cap of 2), preserving message
alternation — no parallel recovery machinery.
Config: agent.stall_guards in DEFAULT_CONFIG; docs in configuration.md;
unit tests for streak/allowlist/reset/gate and detector pos/neg cases.
delegate_task gains a control plane: action='list' / 'steer' / 'stop'
let the parent agent see, redirect, and early-stop its own running
subagents mid-flight — the model-facing counterpart of the TUI's
delegation.pause / subagent.interrupt / subagent.steer RPCs.
- action='list': live children of this conversation's spawn tree
(ids, goal, status, running_seconds, accepting_steer, live
transcript path). Ownership is enforced via a _delegate_parent_ref
weakref chain stamped at child build time, so a conversation can
only control its own descendants, never a sibling tree.
- action='steer': queues text into a running child via the existing
steer_subagent() registry path (delivered at the child's next tool
boundary; missed steers surface as missed_steer in the completion).
- action='stop': interrupt_subagent() — child stops at its next
iteration boundary, partial result still re-enters as a completion.
- Spawn dispatch response now includes subagent_ids + control hint.
- Control actions run synchronously (never backgrounded) and bypass
the spawn pause gate and depth limit; they also never consume the
per-turn subagent spawn cap, and remain usable once the cap is hit
(that is when stop matters most).
- Small-model robustness (found live with gpt-5.4-mini on Nous
Portal): tasks=[] alongside goal no longer trips the "Batch mode
requires at least 2 tasks" gate — treated as single-goal.
- CLI display: control calls render as "steer sa-…" / "list" instead
of an empty goal.
Live-tested E2E on Nous Portal (fable-5 + gpt-5.4-mini): full
spawn→list→steer→stop cycle, plus a steer-efficacy run where the
child acked the steer mid-essay and switched topics before finishing.
Per Teknium: the caps should bound a single agent loop, not accumulate
over the whole session. Rename SessionCapConfig -> LoopCapConfig and the
config section session_caps -> loop_caps; move the counters into
reset_for_turn (invoked per turn via turn_context) so each turn starts
with a fresh budget; retune defaults 200 -> 50 (a single turn issuing 50
web searches / spawning 50 subagents is already pathological). Block
codes session_*_cap -> loop_*_cap and messages updated to drop the
/new-resets-the-budget guidance (irrelevant now that it resets per turn).
Tests flipped: the old persists-across-turn-resets assertion becomes
resets-each-turn.
Add per-session lifetime caps on web_search calls and subagent spawns
(defaults 200/200, matching Claude Code v2.1.212). Unlike the existing
per-turn tool-loop guardrails, these count over the whole session and
reset only when a fresh agent is built (/new, /clear). Hitting a cap
blocks the offending call and halts the turn cleanly.
- agent/tool_guardrails.py: SessionCapConfig + session counters on the
controller (in __init__, not reset_for_turn, so they persist across
turns). before_call() enforces caps first, independent of
hard_stop_enabled. delegate_task batches count each task.
- hermes_cli/config.py: tool_loop_guardrails.session_caps defaults.
- docs + tests (unit + E2E validated against a real AIAgent).
Tool results scraped from the web/social platforms can carry unpaired
UTF-16 surrogates (e.g. half of a mathematical-bold character pair).
_sha256() did a strict utf-8 encode, which raises UnicodeEncodeError on
that input and took down the whole conversation loop — the hash only
needs deterministic bytes, not valid UTF-8, so encode with
surrogatepass instead.
The initial guardrail PR consolidated failure classification by pointing
display._detect_tool_failure at the new classify_tool_failure helper,
which was strictly broader: it flagged any JSON result with
"success": false / "failed": true / non-empty "error", plus plain-text
"traceback" and "error:" prefixes. That would uptick the user-visible
[error] tag on tools that return {"success": false} as a benign signal
(memory fullness, todo state, etc.) and feed the failure-streak counter
at the same time.
Restore display._detect_tool_failure to its pre-PR semantics verbatim.
Tighten classify_tool_failure (the guardrail's internal safety-fallback
used only when callers don't pass failed=) to match _detect_tool_failure
exactly, so the two never disagree. Production callers in run_agent.py
already pass an explicit failed= derived from _detect_tool_failure, so
the guardrail counter is driven by the same signal the CLI shows.
Teknium