mirror of
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240 lines
9.8 KiB
Python
240 lines
9.8 KiB
Python
"""
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Loop detection for the browser sub-agent.
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Tracks recent state-mutating tool calls in a sliding window. If the model
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repeats the same (tool, input) with the same result several times, we inject
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an is_error message in the next tool_result to force a strategy change. This
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prevents the model from burning the entire turn budget on a failing approach.
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"""
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import json
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# Tools that are read-only / idempotent and should NOT count toward loop
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# detection. Repeating these is normal (scrolling through a feed, taking
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# successive screenshots, polling for an element to appear).
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_LOOP_DETECTION_EXCLUDED_TOOLS = {
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"BrowserScreenshot",
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"BrowserGetText",
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"BrowserGetElements",
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"BrowserListInteractives", # Phase 3
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"BrowserWait",
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"ReportProgress", # Phase 2
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"RequestHumanIntervention",
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"BrowserListSkills", # meta: inspect own learned skills
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"BrowserDeprecateSkill", # meta: prune a stale skill
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}
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_LOOP_WINDOW_SIZE = 5
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_LOOP_REPEAT_THRESHOLD = 3
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_LOOP_HARD_CAP = 5
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def _hash_tool_call(tool_name: str, tool_input: dict, result: dict) -> tuple[str, str, str]:
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"""Build a stable hash key for a tool call, including its result.
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Including the result hash means that legitimate progress (same input,
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different output; e.g. BrowserScroll on a long feed) does NOT count
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as a loop. Only same-input + same-output is treated as stuck.
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"""
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try:
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input_key = json.dumps(tool_input, sort_keys=True, default=str)
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except Exception:
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input_key = repr(tool_input)
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try:
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# Truncate the result hash to avoid huge image blobs in the key
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result_key = json.dumps(result, sort_keys=True, default=str)[:300]
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except Exception:
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result_key = repr(result)[:300]
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return (tool_name, input_key, result_key)
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def _detect_loop(
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recent_calls: list[tuple[str, str, str]],
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new_call: tuple[str, str, str],
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) -> bool:
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"""Return True if `new_call` constitutes a loop given recent history.
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A loop is when the same (tool, input, result) has appeared at least
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`_LOOP_REPEAT_THRESHOLD` times within the last `_LOOP_WINDOW_SIZE`
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state-mutating calls (the new call counts as one of those occurrences).
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"""
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if new_call[0] in _LOOP_DETECTION_EXCLUDED_TOOLS:
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return False
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window = recent_calls[-(_LOOP_WINDOW_SIZE - 1):] + [new_call]
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matches = sum(1 for c in window if c == new_call)
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return matches >= _LOOP_REPEAT_THRESHOLD
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_LOOP_WARNING_TEXT = (
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"LOOP DETECTED: You have called this tool with these exact parameters and "
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"gotten the same result {count} times in a row. STOP retrying this approach "
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", it is not working. Try a fundamentally different strategy: "
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"(1) check the page state with BrowserScreenshot or BrowserGetText, "
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"(2) try a different selector or a different tool, "
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"(3) use BrowserPressKey for keyboard shortcuts if the site supports them, "
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"or (4) call RequestHumanIntervention if you genuinely cannot proceed."
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)
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# --- Stagnation detection -------------------------------------------------
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# Distinct from the exact-repeat loop above. The agent can be "busy but stuck":
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# trying selector A, then B, then C, all failing. The inputs differ so the
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# exact-repeat detector never fires, yet the page never changes. We watch for a
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# run of state-mutating actions that produced no URL change AND looked like
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# failures (or just repeated the same observation), and nudge the model down
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# the strategy ladder before it burns the whole turn budget.
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# Read-only / meta tools don't count toward stagnation (same exemption set as
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# the loop detector): re-orienting is not "being stuck".
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_STAGNATION_NEUTRAL_TOOLS = _LOOP_DETECTION_EXCLUDED_TOOLS
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_STAGNATION_ESCALATION_AT = 3
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_STAGNATION_MAX = 5
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_FAILURE_MARKERS = (
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"error", "not found", "no longer valid", "no box model",
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"no valid bounding rect", "failed", "rejected", "timed out",
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"could not", "unable to", "denied",
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)
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def _looks_like_failure(text: str) -> bool:
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low = text.lower()
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return any(m in low for m in _FAILURE_MARKERS)
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def is_unproductive(
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tool_name: str, result: dict, prev_url: str, prev_text: str,
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) -> bool:
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"""True if a state-mutating action changed nothing observable.
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Productive (returns False): a URL change, or a success-shaped result, gets
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the benefit of the doubt (a click that opens a dropdown changes no URL but
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is real progress). Unproductive (returns True): an error result, a
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failure-shaped message, or the exact same observation as the previous
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action, all with no URL change. Neutral tools (screenshot, get_text, etc.)
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never count.
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"""
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if tool_name in _STAGNATION_NEUTRAL_TOOLS:
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return False
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new_url = str(result.get("url") or "")
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if new_url and prev_url and new_url != prev_url:
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return False
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if "error" in result:
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return True
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text = str(result.get("text") or result.get("error") or "")
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if _looks_like_failure(text):
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return True
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if prev_text and text[:200] == prev_text[:200]:
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return True
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return False
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_STAGNATION_NUDGE = (
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"NO PROGRESS: your last {streak} actions changed nothing on the page and "
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"looked like failures. STOP repeating this approach. Walk DOWN the strategy "
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"ladder: switch from CSS clicks to BrowserListInteractives + "
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"BrowserClickIndex; if that already failed, try BrowserPressKey (Tab/Enter) "
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"or use BrowserEvaluate to find the element by its visible text; take ONE "
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"BrowserScreenshot to re-orient if you are unsure what's on screen."
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)
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def stagnation_nudge(streak: int) -> str:
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base = _STAGNATION_NUDGE.format(streak=streak)
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if streak >= _STAGNATION_MAX:
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base += (
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" If nothing here works, call RequestHumanIntervention instead of "
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"continuing to fail."
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)
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return base
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def advance_stagnation(
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streak: int, prev_url: str, prev_text: str, tool_name: str, result: dict,
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) -> tuple[int, str, str, str | None]:
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"""Advance the stagnation streak for one executed tool.
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Neutral read/meta tools pass through unchanged (no bump, no reset). For a
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state-mutating action, bump the streak when unproductive else reset it, and
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return a nudge string when the streak crosses an escalation threshold.
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Returns (new_streak, new_prev_url, new_prev_text, nudge_or_None).
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"""
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if tool_name in _STAGNATION_NEUTRAL_TOOLS:
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return streak, prev_url, prev_text, None
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if is_unproductive(tool_name, result, prev_url, prev_text):
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streak += 1
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else:
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streak = 0
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new_url = str(result.get("url") or "") or prev_url
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new_text = str(result.get("text") or result.get("error") or "")[:200]
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nudge = (
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stagnation_nudge(streak)
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if streak in (_STAGNATION_ESCALATION_AT, _STAGNATION_MAX)
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else None
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)
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return streak, new_url, new_text, nudge
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def stagnation_exhausted(streak: int) -> bool:
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"""True once deterministic nudging has been exhausted; the caller may then
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escalate to a one-shot aux-LLM adjudication (see browser_validator)."""
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return streak >= _STAGNATION_MAX
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# --- completion honesty gate ----------------------------------------------
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# A model that ends its turn is NOT proof the goal happened. The worst ghost we
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# measured: multi-minute runs where every tool errored, still reported
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# "completed". This deterministic gate reality-checks the run before we let the
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# status say "done", so a fake success is reported as the failure it actually is.
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# State-changing tools: a task that needed to DO something must land one of these.
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_PRODUCTIVE_TOOLS = {
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"BrowserClick", "BrowserClickIndex", "BrowserType", "BrowserNavigate",
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"BrowserPressKey", "BrowserScroll", "BrowserBatch",
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}
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# Read/extract tools: a look-only task's evidence is that a read returned content.
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_READ_TOOLS = {
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"BrowserGetText", "BrowserGetElements", "BrowserListInteractives",
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"BrowserListRoutes", "BrowserReplayRoute", "BrowserScreenshot", "BrowserEvaluate",
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}
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# A card whose webview is gone is UNRECOVERABLE by the agent (it cannot resurrect
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# the card), unlike a missing selector it could route around. The frontend
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# returns these only AFTER a 2s re-register grace, so they mean the card is truly
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# gone (closed) or the dashboard was never open. Retrying just burns the turn
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# budget (the multi-minute spins we measured), so the caller fails fast instead.
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_CARD_GONE_MARKERS = ("not an electron webview", "no dashboard is connected")
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_CARD_GONE_LIMIT = 2 # consecutive misses before we give up (absorbs a transient)
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def card_is_unavailable(result: dict) -> bool:
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err = str(result.get("error") or "").lower()
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return any(m in err for m in _CARD_GONE_MARKERS)
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def completion_is_honest(action_log: list[dict]) -> tuple[bool, str]:
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"""Reality-check a run the model declared done. Returns (honest, reason).
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Conservative by design (it can flip a 'completed' into an error, so it must
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not cry wolf on a real success): it flags ONLY the unambiguous ghosts, a run
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that took zero actions, one whose every state-changing action errored, or one
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that only looked around (no action and no read returned content). A read-only
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task stays honest as long as some read came back with content; a partially
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erroring run that still landed a real action stays honest.
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"""
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if not action_log:
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return False, "declared done without taking a single action"
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actions = [a for a in action_log if a.get("tool") in _PRODUCTIVE_TOOLS]
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actions_ok = [a for a in actions if a.get("ok")]
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reads_ok = [
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a for a in action_log
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if a.get("tool") in _READ_TOOLS and a.get("ok")
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and str(a.get("result_summary") or "").strip()
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]
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if actions and not actions_ok:
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return False, "every state-changing action failed"
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if not actions and not reads_ok:
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return False, "only looked around: no action taken and no content read back"
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return True, ""
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