fix: checkpoint Kanban completion before tool access expires

Give dispatcher-owned workers a tool-capable reporting opportunity before the
hard iteration cap, without accepting arbitrary diffs or weakening failure
counting. Add opt-in per-turn iteration checkpoints for ordinary agents.
Persist checkpoint text with the fresh tool result, never rewrite cached rows.

Salvages the opt-in ratio and per-turn reset implementation from #104683;
credits the earlier default-off signpost proposal in #92438.

Local fixture wire A/B: Kanban ready/1 failure -> done/0; deliberately stuck
workers still reach blocked/2 after two runs. Default-off control unchanged.
Targeted and affected-directory suites queued behind campaign test lock.

Co-authored-by: fangliquanflq <fangliquan@qq.com>
Co-authored-by: C. Michael Gibbs <252231331+MikeGibbsOnyx@users.noreply.github.com>

agent/agent_init.py

@@ -10,6 +10,7 @@ Symbols that tests patch on ``run_agent.*`` (``OpenAI``, ``get_tool_definitions`
 from __future__ import annotations
 
 import logging
+import math
 import os
 import re
 import sys
@@ -317,6 +318,17 @@ def _normalize_run_budget_seconds(value) -> Optional[float]:
     return seconds if seconds > 0 else None  # NaN compares False → None
 
 
+def _normalize_budget_warning_ratio(value) -> Optional[float]:
+    """A finite ratio strictly between zero and one, or None (feature off)."""
+    if value is None or isinstance(value, bool):
+        return None
+    try:
+        ratio = float(value)
+    except (TypeError, ValueError):
+        return None
+    return ratio if math.isfinite(ratio) and 0 < ratio < 1 else None
+
+
 def _refuse_checkpoint_required_on_codex_app_server(
     checkpoint_required: bool, api_mode: Optional[str]
 ) -> None:
@@ -536,8 +548,9 @@ _CONTROL_STATE: Dict[str, Any] = {
 
 # Per-turn bookkeeping: budgets, activity tracking, rate-limit/credits telemetry.
 _TURN_STATE: Dict[str, Any] = {
-    # Iteration budget: notify the LLM only on exhaustion (one message, one grace call, then
-    # a forced summary) — intermediate pressure warnings made models give up early.
+    # Intermediate pressure warnings made models give up early; ordinary conversations
+    # remain opt-in. Dispatcher workers receive a bounded completion checkpoint.
+    "_iteration_budget_warning_injected": False,
     "_budget_exhausted_injected": False,
     "_budget_grace_call": False,
     "_run_budget_started_at": None,  # set by turn_context.prepare_turn when a budget is active
@@ -1307,6 +1320,9 @@ def _apply_agent_section(agent, _agent_cfg):
         agent._skill_nudge_interval = int(_agent_cfg.get("skills", {}).get("creation_nudge_interval", 10))
 
     _agent_section = _cfg_dict(_agent_cfg, "agent")
+    agent.budget_warning_ratio = _normalize_budget_warning_ratio(
+        _agent_section.get("budget_warning_ratio")
+    )
     # Both: "auto" (model-list match), true, false, or list of model substrings; independent
     # of each other (gates in agent/system_prompt.py).
     agent._tool_use_enforcement = _agent_section.get("tool_use_enforcement", "auto")

agent/tool_executor.py

@@ -173,6 +173,11 @@ def _resolve_concurrent_tool_timeout() -> float | None:
 def _flush_session_db_after_tool_progress(agent, messages: list, *, stage: str) -> bool:
     """Flush tool-call progress to the session DB before projecting it to any UI: tool side
     effects can kill/restart the process before turn-end persistence runs."""
+    from agent.turn_iteration_prep import _maybe_inject_iteration_budget_warning
+
+    # Persist exactly the checkpoint text the next model call will see, before stamping
+    # this tool result as durable. Already-written rows must never be rewritten later.
+    _maybe_inject_iteration_budget_warning(agent, messages)
     try:
         persisted = agent._flush_messages_to_session_db(messages) is not False
         if not persisted:

agent/turn_context.py

@@ -442,6 +442,7 @@ _PER_TURN_RESET_STATE: Tuple[Tuple[str, Any], ...] = (
     ("_last_content_with_tools", None), ("_last_content_tools_all_housekeeping", False),
     ("_mute_post_response", False), ("_unicode_sanitization_passes", 0),
     ("_tool_guardrail_halt_decision", None), ("_vision_supported", True),
+    ("_iteration_budget_warning_injected", False),
     ("_run_budget_wrapup_injected", False), ("_verification_stop_nudges", 0),
     ("_pre_verify_nudges", 0),
 )

agent/turn_iteration_prep.py

@@ -11,6 +11,7 @@ from __future__ import annotations
 
 import logging
 import random
+import sys
 from contextlib import suppress
 from dataclasses import dataclass
 from typing import Any, Dict
@@ -20,6 +21,61 @@ from agent.turn_context import reanchor_current_turn_user_idx
 
 logger = logging.getLogger("agent.conversation_loop")
 
+ITERATION_BUDGET_WARNING_TEMPLATE = (
+    "[SYSTEM NOTICE — iteration budget checkpoint] You have used {used} of {maximum} "
+    "iterations. Checkpoint durable progress now, then continue the task; do not stop "
+    "solely because of this warning."
+)
+
+
+def _maybe_inject_iteration_budget_warning(agent: Any, messages: Any) -> bool:
+    """Append the opt-in one-shot warning to the newest tool result."""
+    import os
+    from agent.delegation_context import is_dispatcher_owned_worker_context
+
+    ratio = getattr(agent, "budget_warning_ratio", None)
+    kanban_worker = (
+        bool(os.environ.get("HERMES_KANBAN_TASK"))
+        and is_dispatcher_owned_worker_context()
+        and "kanban_complete" in getattr(agent, "valid_tool_names", ())
+    )
+    if ratio is None and kanban_worker:
+        ratio = 0.9
+    budget = getattr(agent, "iteration_budget", None)
+    if (
+        ratio is None
+        or budget is None
+        or budget.max_total <= 1
+        or budget.max_total >= sys.maxsize
+        or getattr(agent, "_iteration_budget_warning_injected", False)
+        or budget.used < min(ratio * budget.max_total, budget.max_total - 1)
+    ):
+        return False
+    notice = ITERATION_BUDGET_WARNING_TEMPLATE.format(
+        used=budget.used, maximum=budget.max_total
+    )
+    if kanban_worker:
+        notice += (
+            " While tools are still available, call kanban_complete only if all task "
+            "requirements are verified; otherwise persist a kanban_comment handoff and "
+            "continue. A diff or commit alone is not completion evidence."
+        )
+    # Only the current tool-result tail is mutable; an older turn may already be cached.
+    from agent.context_compressor import _DB_PERSISTED_MARKER
+    if (not messages or messages[-1].get("role") != "tool"
+            or messages[-1].get(_DB_PERSISTED_MARKER)):
+        return False
+    message = messages[-1]
+    content = message.get("content", "")
+    if isinstance(content, str):
+        message["content"] = content + f"\n\n{notice}"
+    elif isinstance(content, list) or content is None:
+        message["content"] = [*(content or []), {"type": "text", "text": notice}]
+    else:
+        return False
+    agent._iteration_budget_warning_injected = True
+    return True
+
 
 @dataclass
 class IterationPrep:
@@ -76,6 +132,9 @@ def prepare_iteration(agent: Any,*, messages: Any, api_call_count: Any) -> Itera
     if getattr(agent, "run_budget_seconds", None):
         _maybe_inject_run_budget_wrapup(agent, messages)
 
+    # Use the same cache-safe channel as /steer; never add a synthetic user/system row.
+    _maybe_inject_iteration_budget_warning(agent, messages)
+
     request_logger = getattr(agent, "logger", None) or logger  # same name as the origin module
     # Per-agent validation cursor skips re-parsing tool_call args already validated.
     # Identity-keyed; a rewritten list breaks the prefix match and forces a re-scan.

hermes_cli/config_defaults.py

@@ -50,6 +50,9 @@ DEFAULT_CONFIG = {
         # Turn cap. null = unlimited (default; caps caused silent mid-task truncation). Positive int
         # caps; "none"/"unlimited"/"inf"/0/-1 also mean unlimited (resolve_turn_limit).
         "max_turns": None,
+        # Optional one-time model-visible checkpoint warning before a finite turn cap is exhausted.
+        # null = off; set a ratio strictly between 0 and 1 (for example, 0.75).
+        "budget_warning_ratio": None,
         # Wall-clock budget (seconds) per run. null = off. When set: one-time wrap-up notice at 80%
         # elapsed; implicit provider stale timeouts capped to remaining budget. CLI equivalent:
         # `hermes chat --run-budget N`.

tests/agent/test_iteration_budget_warning.py

@@ -0,0 +1,52 @@
+"""Iteration checkpoints preserve the transcript and the hard budget."""
+from copy import deepcopy
+
+import pytest
+
+
+def _agent(tmp_path, monkeypatch, ratio):
+    monkeypatch.setenv("HERMES_HOME", str(tmp_path))
+    (tmp_path / "config.yaml").write_text(
+        f"agent:\n  budget_warning_ratio: {ratio}\n", encoding="utf-8"
+    )
+    from run_agent import AIAgent
+    return AIAgent(model="test-model", provider="openai-compat", api_key="test",
+                   base_url="http://127.0.0.1:1/v1", max_iterations=4,
+                   quiet_mode=True, skip_context_files=True, skip_memory=True)
+
+
+@pytest.mark.parametrize("ratio", ["null", "true", "0", "1", ".nan", "junk", "0.75"])
+def test_checkpoint_is_opt_in_and_does_not_rewrite_prior_turns(tmp_path, monkeypatch, ratio):
+    from agent.turn_iteration_prep import prepare_iteration
+    agent = _agent(tmp_path, monkeypatch, ratio)
+    for _ in range(3):
+        agent.iteration_budget.consume()
+    messages = [{"role": "user", "content": "work"},
+                {"role": "assistant", "tool_calls": [{"id": "t", "type": "function", "function": {"name": "read_file", "arguments": "{}"}}]},
+                {"role": "tool", "tool_call_id": "t", "content": "result"}]
+    original = deepcopy(messages)
+    prepare_iteration(agent, messages=messages, api_call_count=3)
+    assert messages[:-1] == original[:-1]
+    assert (messages[-1]["content"] != "result") == (ratio == "0.75")
+    snapshot = deepcopy(messages)
+    prepare_iteration(agent, messages=messages, api_call_count=3)
+    assert messages == snapshot
+    assert agent.iteration_budget.used == 3
+
+
+@pytest.mark.parametrize("content", ["result", [{"type": "text", "text": "result"}]])
+def test_checkpoint_rearms_per_turn_with_tools_still_available(tmp_path, monkeypatch, content):
+    from agent.turn_context import _reset_per_turn_agent_state
+    from agent.turn_iteration_prep import prepare_iteration
+    agent = _agent(tmp_path, monkeypatch, "0.75")
+    for _ in range(2):
+        _reset_per_turn_agent_state(agent)
+        for _ in range(3):
+            agent.iteration_budget.consume()
+        messages = [{"role": "user", "content": "work"},
+                    {"role": "assistant", "tool_calls": [{"id": "t", "type": "function", "function": {"name": "read_file", "arguments": "{}"}}]},
+                    {"role": "tool", "tool_call_id": "t", "content": deepcopy(content)}]
+        prepare_iteration(agent, messages=messages, api_call_count=3)
+        assert "3 of 4" in str(messages[-1]["content"])
+        assert agent.iteration_budget.consume()
+        assert not agent.iteration_budget.consume()

tests/agent/test_kanban_budget_checkpoint.py

@@ -0,0 +1,19 @@
+import pytest
+from tests.agent.test_iteration_budget_warning import _agent
+
+@pytest.mark.parametrize("owned", [True, False])
+def test_kanban_checkpoint_is_only_for_dispatcher_owner(tmp_path, monkeypatch, owned):
+    from agent.delegation_context import non_dispatcher_owned_context
+    from contextlib import nullcontext
+    from agent.turn_iteration_prep import prepare_iteration
+    monkeypatch.setenv("HERMES_KANBAN_TASK", "t_checkpoint")
+    with nullcontext() if owned else non_dispatcher_owned_context():
+        agent = _agent(tmp_path, monkeypatch, "null")
+        for _ in range(4):
+            agent.iteration_budget.consume()
+        messages = [{"role": "user", "content": "work"},
+                    {"role": "assistant", "tool_calls": [{"id": "t", "type": "function", "function": {"name": "read_file", "arguments": "{}"}}]},
+                    {"role": "tool", "tool_call_id": "t", "content": "verified artifact"}]
+        prepare_iteration(agent, messages=messages, api_call_count=4)
+        assert ("kanban_complete" in messages[-1]["content"]) is owned
+        assert agent.iteration_budget.remaining == 0

website/docs/user-guide/configuration.md

@@ -1133,11 +1133,14 @@ agent:
   max_turns: none              # Iterations per conversation turn (default: none = unlimited)
                                # Set a positive integer to cap; "none"/"null"/
                                # "unlimited"/"inf"/"infinity"/"infinite"/0/-1 = no limit
+  budget_warning_ratio: null   # Optional one-time checkpoint warning, e.g. 0.75
   api_max_retries: 3           # Retries per provider before fallback engages (default: 3)
 ```
 
 `agent.max_turns` is **unlimited by default** — the turn cap caused more problems than it solved (silent mid-task truncation), so out of the box Hermes runs a conversation turn to completion. To impose a cap, set a positive integer. To be explicit about "no limit", any of these case-insensitive spellings work: `"none"`, `"null"`, `"unlimited"`, `"infinite"`, `"infinity"`, `"inf"`, `0`, `-1` (they resolve to a `sys.maxsize` sentinel so the loop never exits on a turn count).
 
+`agent.budget_warning_ratio` is off by default for ordinary and delegated conversations. When set to a value strictly between `0` and `1` alongside a finite `max_turns`, Hermes appends one model-visible checkpoint notice to the latest tool result after the threshold is reached. The notice rearms each conversation turn and uses each agent's own iteration budget. It only appends to a current tool-result tail, never an older turn, and does not add a synthetic user/system message or change the existing exhaustion grace call. Dispatcher-owned Kanban workers receive a completion checkpoint at 90% by default (an explicit ratio changes that threshold), while their tools are still available. The checkpoint asks for verified completion or a durable progress comment, not premature success.
+
 `agent.api_max_retries` controls how many times Hermes retries a provider API call on transient errors (rate limits, connection drops, 5xx) **before** fallback-provider switching engages. The default is `3` — four attempts total. If you have [fallback providers](/user-guide/features/fallback-providers) configured and want to fail over faster, drop this to `0` so the first transient error on your primary immediately hands off to the fallback instead of churning retries against the flaky endpoint.
 
 ## Wall-Clock Run Budget

website/docs/user-guide/features/kanban.md

@@ -10,6 +10,22 @@ description: "Durable SQLite-backed task board for coordinating multiple Hermes
 
 Hermes Kanban is a durable task board, shared across all your Hermes profiles, that lets multiple named agents collaborate on work without fragile in-process subagent swarms. Every task is a row in `~/.hermes/kanban.db`; every handoff is a row anyone can read and write; every worker is a full OS process with its own identity.
 
+### Completion checkpoints before the iteration cap
+
+Dispatcher-owned workers get one checkpoint notice near 90% of their finite iteration
+budget, attached to a fresh tool result while another tool-capable call remains. Use
+`agent.budget_warning_ratio` to choose an earlier threshold. Tiny budgets warn no later
+than their penultimate iteration; a one-iteration run has no pre-cap checkpoint window.
+The notice is saved in the session transcript before the next request. Workers should
+call `kanban_complete` only after verifying the task contract, or persist a progress
+comment and continue. A commit or diff alone never automatically completes a task.
+
+The hard cap, toolless final summary, and consecutive-failure circuit breaker are
+unchanged: workers that still exhaust their budget remain subject to bounded retries.
+This is a reporting opportunity, not a guarantee that a model will heed the notice.
+Ordinary conversations and delegated children do not inherit the automatic Kanban
+checkpoint; their iteration warning remains opt-in.
+
 ### Two surfaces: the model talks through tools, you talk through the CLI
 
 The board has two front doors, both backed by the same `~/.hermes/kanban.db`: