/home/llmeval/.local/share/uv/tools/cubbi/lib/python3.12/site-packages/click/core.py:1213: UserWarning: The parameter -m is used more than once. Remove its duplicate as parameters should be unique. parser = self.make_parser(ctx) /home/llmeval/.local/share/uv/tools/cubbi/lib/python3.12/site-packages/click/core.py:1206: UserWarning: The parameter -m is used more than once. Remove its duplicate as parameters should be unique. self.parse_args(ctx, args) Using UID: 1000, GID: 1000 Forwarding environment variable OPENROUTER_API_KEY to container Mounting local directory /home/llmeval/llmeval/runs/run_20260121_150059/task11_relationship_classifier/openrouter-google-gemini-2.5-flash-preview-09-2025/workspace to /app No project_name provided - skipping configuration directory setup. Session created successfully! Session ID: 2aa1240e Image: opencode Executing command and waiting for completion... Container will exit after command completes. Command logs: Initializing opencode v1.0.0 Setting up user 'cubbi' with UID: 1000, GID: 1000 Setting up standard directories Created directory: /app Created directory: /cubbi-config Created directory: /cubbi-config/home Creating /home/cubbi as symlink to /cubbi-config/home Created directory: /cubbi-config/home/.local Copied /root/.local/bin to user directory Running opencode-specific initialization Added litellm custom provider with 159 models to OpenCode configuration Added openrouter standard provider with 344 models to OpenCode configuration Set default model to openrouter/google/gemini-2.5-flash-preview-09-2025 Updated OpenCode configuration at /home/cubbi/.config/opencode/config.json with 2 providers No MCP servers to integrate --- Executing initial command --- Executing user command: if [ -f install.sh ]; then bash install.sh; fi; echo "--- TASK BEGIN ---"; cat task.md; echo "--- TASK END ---"; cd input && opencode run --print-logs < ../task.md Executing as cubbi: sh -c if [ -f install.sh ]; then bash install.sh; fi; echo "--- TASK BEGIN ---"; cat task.md; echo "--- TASK END ---"; cd input && opencode run --print-logs < ../task.md --- TASK BEGIN --- # Relationship Classifier Task You are given a relationship classification prompt and a set of test cases. Your task is to act as an LLM classifier and classify each test case according to the provided prompt guidelines. ## Prompt Variables | Variable | Type | Description | | ------------------------------- | ---- | ------------------------------------------------------- | | `primary_name` | str | Name of the primary profile | | `primary_headline` | str | Title/headline of the primary profile | | `primary_bio` | str | Bio of the primary profile | | `candidate_name` | str | Name of the candidate profile | | `candidate_headline` | str | Title/headline of the candidate profile | | `candidate_bio` | str | Bio of the candidate profile | | `interaction_type` | str | Either "candidate_on_primary" or "primary_on_candidate" | | `post_text` | str | The post content (truncated to 500 chars) | | `comment_text` | str | The comment content | | `engagement.totalReactionCount` | int | Number of reactions on the post | | `engagement.totalComments` | int | Number of comments/replies on the post | ## Instructions 1. Read the `classifier_prompt.md` file to understand the classification criteria 2. Read the `test_cases.json` file containing 20 LinkedIn interaction scenarios 3. For each test case, determine whether the two people **know each other personally** based on: - The profiles of both people - The interaction type (who commented on whose post) - The post content - The comment content - The engagement metrics 4. Output your classifications to a file named `results.json` with the following format: ```json { "classifications": [ {"case_index": 0, "knows_each_other": true}, {"case_index": 1, "knows_each_other": false}, ... ] } ``` The `case_index` should match the index of each test case in the `test_cases.json` array (0-indexed). ## Key Classification Guidelines (from the prompt) **Strong Evidence (suggests they know each other):** - Personal familiarity in tone or language - References to shared experiences, meetings, or conversations - Inside jokes or personal nicknames - Mentions of non-work related interactions - Direct personal questions or congratulations - Collaborative language suggesting ongoing relationship **Weak Evidence (suggests they might NOT know each other):** - Generic professional comments ("Great post!", "Thanks for sharing") - Purely transactional or informational exchanges - Formal, distant tone - No personalization or specific references Be objective and evidence-based. Professional courtesy does NOT equal personal connection. PS: You are currently working in an automated system and cannot ask any questions or have back and forth with a user. --- TASK END --- INFO 2026-01-21T15:10:46 +759ms service=default version=1.1.17 args=["run","--print-logs"] opencode INFO 2026-01-21T15:10:46 +5ms service=default directory=/app/input creating instance INFO 2026-01-21T15:10:46 +1ms service=project directory=/app/input fromDirectory INFO 2026-01-21T15:10:46 +4ms service=storage index=0 running migration ERROR 2026-01-21T15:10:46 +4ms service=storage index=0 failed to run migration INFO 2026-01-21T15:10:46 +1ms service=storage index=1 running migration INFO 2026-01-21T15:10:46 +5ms service=default directory=/app/input bootstrapping INFO 2026-01-21T15:10:46 +5ms service=config path=/home/cubbi/.config/opencode/config.json loading INFO 2026-01-21T15:10:46 +59ms service=config path=/home/cubbi/.config/opencode/opencode.json loading INFO 2026-01-21T15:10:46 +0ms service=config path=/home/cubbi/.config/opencode/opencode.jsonc 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cmd=["/opt/node/lib/node_modules/opencode-ai/node_modules/opencode-linux-x64/bin/opencode","add","--force","--exact","--cwd","/home/cubbi/.cache/opencode","opencode-anthropic-auth@0.0.8"] cwd=/home/cubbi/.cache/opencode running INFO 2026-01-21T15:10:47 +603ms service=bun code=0 stdout=bun add v1.3.5 (1e86cebd) + opencode-copilot-auth@0.0.12 installed opencode-anthropic-auth@0.0.8 14 packages installed [591.00ms] stderr=Resolving dependencies Resolved, downloaded and extracted [50] Saved lockfile done INFO 2026-01-21T15:10:47 +62ms service=bus type=* subscribing INFO 2026-01-21T15:10:47 +0ms service=bus type=session.updated subscribing INFO 2026-01-21T15:10:47 +0ms service=bus type=message.updated subscribing INFO 2026-01-21T15:10:47 +0ms service=bus type=message.part.updated subscribing INFO 2026-01-21T15:10:47 +0ms service=bus type=session.updated subscribing INFO 2026-01-21T15:10:47 +0ms service=bus type=message.updated subscribing INFO 2026-01-21T15:10:47 +0ms service=bus 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ruleset=[{"permission":"*","pattern":"*","action":"allow"},{"permission":"doom_loop","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","pattern":"*","action":"deny"},{"permission":"read","pattern":"*","action":"allow"},{"permission":"read","pattern":"*.env","action":"ask"},{"permission":"read","pattern":"*.env.*","action":"ask"},{"permission":"read","pattern":"*.env.example","action":"allow"},{"permission":"question","pattern":"*","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"}] evaluate INFO 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ruleset=[{"permission":"*","pattern":"*","action":"allow"},{"permission":"doom_loop","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","pattern":"*","action":"deny"},{"permission":"read","pattern":"*","action":"allow"},{"permission":"read","pattern":"*.env","action":"ask"},{"permission":"read","pattern":"*.env.*","action":"ask"},{"permission":"read","pattern":"*.env.example","action":"allow"},{"permission":"question","pattern":"*","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"}] evaluate INFO 2026-01-21T15:10:49 +0ms service=permission permission=read pattern=/app/input/test_cases.json action={"permission":"read","pattern":"*","action":"allow"} evaluated INFO 2026-01-21T15:10:49 +37ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:10:49 +4ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:10:49 +6ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:10:49 +5ms service=lsp file=/app/input/test_cases.json touching file INFO 2026-01-21T15:10:49 +5ms service=file.time sessionID=ses_41ee44c29ffemXANyVkM1ZprP3 file=/app/input/test_cases.json read INFO 2026-01-21T15:10:49 +32ms service=bus type=message.part.updated publishing I need to first read the `classifier_prompt.md` and `test_cases.json` files to understand the classification criteria and the data. I'll use the `read` tool to get the content of both files. INFO 2026-01-21T15:10:49 +7ms service=bus type=message.part.updated publishing |  Read app/input/test_cases.json INFO 2026-01-21T15:10:49 +8ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:10:49 +1ms service=bus type=message.updated publishing INFO 2026-01-21T15:10:49 +16ms service=bus type=message.updated publishing INFO 2026-01-21T15:10:49 +0ms service=bus type=session.status publishing INFO 2026-01-21T15:10:49 +0ms service=session.prompt step=1 sessionID=ses_41ee44c29ffemXANyVkM1ZprP3 loop INFO 2026-01-21T15:10:49 +5ms service=bus type=message.updated publishing INFO 2026-01-21T15:10:49 +1ms service=llm providerID=openrouter modelID=anthropic/claude-haiku-4.5 sessionID=ses_41ee44c29ffemXANyVkM1ZprP3 small=true agent=title stream INFO 2026-01-21T15:10:49 +2ms service=bus type=session.updated publishing INFO 2026-01-21T15:10:49 +0ms service=bus type=session.diff publishing INFO 2026-01-21T15:10:49 +14ms service=bus type=message.updated publishing INFO 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checking INFO 2026-01-21T15:11:01 +0ms service=format name=cargofmt ext=.json checking INFO 2026-01-21T15:11:01 +0ms service=format name=biome ext=.json checking INFO 2026-01-21T15:11:01 +3ms service=bus type=message.part.updated publishing The first tool call failed because `classifier_prompt.md` was not found. I'll ask for the contents of the prompt directly. Since I have the `test_cases.json` content, I can proceed with the task once I get the prompt information. However, the task instruction is clear: I need to act as an LLM classifier and classify each test case. The prompt guidelines were already summarized in the instructions, so I will rely on those until I get the full `classifier_prompt.md`. **Key Classification Guidelines (from the prompt - as per instructions):** **Strong Evidence (suggests they know each other):** - Personal familiarity in tone or language - References to shared experiences, meetings, or conversations - Inside jokes or personal nicknames - Mentions of non-work related interactions - Direct personal questions or congratulations - Collaborative language suggesting ongoing relationship **Weak Evidence (suggests they might NOT know each other):** - Generic professional comments ("Great post!", "Thanks for sharing") - Purely transactional or informational exchanges - Formal, distant tone - No personalization or specific references I will now process the 20 test cases from the provided JSON content. --- ### Classification Analysis I will analyze the `comment_text` for strong evidence of a personal connection, particularly looking for: 1. **Personal names/nicknames** (e.g., "Sarah!", "Rach", "Liv", "Will!!!", "Jess") 2. **Shared past experiences** (e.g., "late nights in 2019", "Google days", "onboarded at LinkedIn 8 years ago") 3. **Non-work references** (e.g., "Drinks soon to celebrate?", "fishing trip promise", "new puppy", "kids are still talking about it", "family dinner soon", "Auntie Alex") 4. **Mention of current plans** (e.g., "Coffee next week", "Let's grab lunch", "Beers next time I'm in Seattle") #### Case 0 * `primary_name`: Sarah Chen * `candidate_name`: Marcus Johnson * `comment_text`: "Sarah! This is amazing - I still remember those late nights in 2019 when we were whiteboarding the first version of this in the old office. So happy to see it finally ship. Drinks soon to celebrate?" * **Analysis**: Uses personal name "Sarah!". References a shared, specific past experience ("late nights in 2019", "old office"). Suggests a personal, non-work interaction ("Drinks soon to celebrate?"). * **Classification**: `true` #### Case 1 * `primary_name`: David Park * `candidate_name`: Jennifer Walsh * `comment_text`: "Congrats David! Well deserved." * **Analysis**: Generic congratulatory comment. No shared experience, personal detail, or follow-up plan. * **Classification**: `false` #### Case 2 * `primary_name`: Rachel Torres * `candidate_name`: Michael Okonkwo * `comment_text`: "Haha Rach, you literally said the same thing at dinner last month and I've been thinking about it ever since. Finally convinced my team to kill our corporate-speak landing pages. You were right (as usual)." * **Analysis**: Uses nickname "Rach". References a non-work interaction ("dinner last month"). Familiar tone. * **Classification**: `true` #### Case 3 * `primary_name`: James Liu * `candidate_name`: Amanda Stevens * `comment_text`: "Great work! This is exactly what the field needs. Looking forward to reading the full paper." * **Analysis**: Purely professional, transactional comment. No personal details. * **Classification**: `false` #### Case 4 * `primary_name`: Emily Richardson * `candidate_name`: Tom Bradley * `comment_text`: "Tom!! I can't believe it. Remember when we both started the same week back in 2016? You've grown so much as a leader. Coffee next week - I want to hear all about what's next. And yes, I'm still holding you to that fishing trip promise ����" * **Analysis**: Uses personal name/nickname "Tom!!". References a specific shared past experience ("started the same week back in 2016"). Mentions a non-work activity/inside joke ("fishing trip promise"). Suggests a future personal meeting ("Coffee next week"). * **Classification**: `true` #### Case 5 * `primary_name`: Kevin Patel * `candidate_name`: Lisa Zhang * `comment_text`: "Thanks for sharing! This is really helpful advice." * **Analysis**: Generic, professional, appreciative comment. No personal details. * **Classification**: `false` #### Case 6 * `primary_name`: Olivia Martinez * `candidate_name`: Robert Kim * `comment_text`: "Liv! Was looking for you at the Andreessen party but couldn't find you in the crowd. Your panel was fantastic - especially the part about patient outcomes. Let's grab lunch when you're back in SF. Also, how's the new puppy adjusting??" * **Analysis**: Uses nickname "Liv!". Mentions a shared social event ("Andreessen party"). Suggests a future personal meeting ("Let's grab lunch"). Asks a direct personal, non-work related question ("how's the new puppy adjusting??"). * **Classification**: `true` #### Case 7 * `primary_name`: Daniel Brown * `candidate_name`: Sophia Lee * `comment_text`: "Congratulations on this milestone! ����" * **Analysis**: Generic, congratulatory comment. No personal details. * **Classification**: `false` #### Case 8 * `primary_name`: Chris Anderson * `candidate_name`: Patricia Nguyen * `comment_text**: "PATRICIA!!! ������������ So incredibly proud of you! I've watched you grow from that nervous new grad I onboarded at LinkedIn 8 years ago to the absolute powerhouse you are today. You earned every bit of this. Dinner's on me - and bring Alex, we need to finally meet this mysterious partner of yours!" * **Analysis**: Uses personal name "PATRICIA!!!". References a specific shared work history ("onboarded at LinkedIn 8 years ago"). Mentions a future social, non-work meeting ("Dinner's on me") and references the candidate's personal partner ("bring Alex, we need to finally meet this mysterious partner of yours!"). * **Classification**: `true` #### Case 9 * `primary_name`: Andrew Thompson * `candidate_name`: Maria Santos * `comment_text`: "Very insightful analysis. Would love to connect and discuss further." * **Analysis**: Generic professional feedback and a standard professional call-to-action ("Would love to connect"). No personal details. * **Classification**: `false` #### Case 10 * `primary_name`: Jessica Williams * `candidate_name`: Brian O'Connor * `comment_text`: "There she is!! 142% is insane Jess, but honestly not surprised. Still can't believe you closed that Walmart deal while we were at your lake house last summer - I remember you taking that call on the dock lol. We need to do that trip again, the kids are still talking about it. Congrats!! ����" * **Analysis**: Uses nickname "Jess". References a specific, non-work related shared event ("while we were at your lake house last summer", "on the dock"). Mentions shared future non-work plans ("We need to do that trip again") and shared personal connections ("the kids are still talking about it"). * **Classification**: `true` #### Case 11 * `primary_name`: Nathan Clark * `candidate_name`: Michelle Davis * `comment_text`: "Interesting approach! Looking forward to reading the technical details." * **Analysis**: Purely professional/technical comment. No personal details. * **Classification**: `false` #### Case 12 * `primary_name`: Laura Chen * `candidate_name`: Steven Wright * `comment_text`: "Steve, this post brought back so many memories from our Google days! Remember when we had to navigate that massive reorg together in 2018? Your calm under pressure taught me so much. Still using the frameworks we built together. Miss working with you - let's catch up soon. How's Emma doing at Berkeley btw?" * **Analysis**: Uses personal name/nickname "Steve". References a specific shared past experience ("our Google days", "massive reorg together in 2018"). Suggests a future personal meeting ("let's catch up soon"). Asks a direct personal question about family ("How's Emma doing at Berkeley btw?"). * **Classification**: `true` #### Case 13 * `primary_name`: Ryan Murphy * `candidate_name`: Angela Foster * `comment_text`: "Great thread! Bookmarking this for future reference. Thanks for sharing your learnings." * **Analysis**: Generic, professional, appreciative comment. No personal details. * **Classification**: `false` #### Case 14 * `primary_name`: Hannah Miller * `candidate_name`: George Adams * `comment_text`: "Hannah, watching your journey has been incredible. I still remember when you pitched this idea to me over coffee right before you left GS - I thought you were crazy but secretly wished I had your courage. So proud of everything you've built. Let's do our annual catch-up dinner soon? Same spot as always?" * **Analysis**: Uses personal name "Hannah". References a specific shared past event ("pitched this idea to me over coffee"). Suggests a recurring, personal future event ("annual catch-up dinner soon? Same spot as always?"). * **Classification**: `true` #### Case 15 * `primary_name`: Tyler Robinson * `candidate_name`: Samantha Brooks * `comment_text`: "Interesting perspective. Would be curious to see some data backing this up." * **Analysis**: Professional, challenging/curious tone about the post's content. No personal details. * **Classification**: `false` #### Case 16 * `primary_name`: Diana Rodriguez * `candidate_name`: William Chang * `comment_text`: "Will!!! 15 years is incredible. You were my first mentor when I joined Amazon in 2015 and honestly you shaped my entire career. Remember when you stayed late for 3 weeks straight helping me debug that inventory system issue? I still use the debugging framework you taught me. You're the reason I became a CTO. Beers next time I'm in Seattle - non-negotiable! ����" * **Analysis**: Uses personal name/nickname "Will!!!". References a specific shared past experience ("first mentor when I joined Amazon in 2015", "stayed late for 3 weeks straight helping me debug"). Highly personal, emotional connection to a shared past. Suggests a future social meeting with familiar tone ("Beers next time I'm in Seattle - non-negotiable!"). * **Classification**: `true` #### Case 17 * `primary_name`: Eric Foster * `candidate_name`: Nicole Baker * `comment_text`: "Some valid points here. Though I think the answer is more nuanced - it depends on the type of work and team culture." * **Analysis**: Professional disagreement/nuance. No personal details. * **Classification**: `false` #### Case 18 * `primary_name`: Alexandra Green * *candidate_name*: Jason Kim * `comment_text`: "Alex!! So proud of you and the team! This reminds me of that crazy launch we did together at Twitter - remember sleeping in the office for 3 days straight? ���� You've always had this ability to rally people. BTW, my daughter loved the birthday gift you sent - she hasn't stopped playing with it. We need to do family dinner soon, the kids keep asking about 'Auntie Alex'" * **Analysis**: Uses nickname "Alex!!". References a specific shared past experience ("crazy launch we did together at Twitter", "sleeping in the office"). Mentions non-work, family-level personal interactions ("daughter loved the birthday gift", "family dinner soon", "Auntie Alex"). * **Classification**: `true` #### Case 19 * `primary_name`: Mark Peterson * `candidate_name`: Katherine Liu * `comment_text`: "Well said. Too many teams get caught up in buzzwords instead of focusing on fundamentals." * **Analysis**: Professional agreement/opinion. No personal details. * **Classification**: `false` --- ### Summary of Classifications | Case Index | Classification | | :--------: | :------------: | | 0 | true | | 1 | false | | 2 | true | | 3 | false | | 4 | true | | 5 | false | | 6 | true | | 7 | false | | 8 | true | | 9 | false | | 10 | true | | 11 | false | | 12 | true | | 13 | false | | 14 | true | | 15 | false | | 16 | true | | 17 | false | | 18 | true | | 19 | false | I will now format this into the required `results.json` structure and write it to a file. INFO 2026-01-21T15:11:01 +8ms service=file.time sessionID=ses_41ee44c29ffemXANyVkM1ZprP3 file=/app/input/results.json read INFO 2026-01-21T15:11:01 +0ms service=lsp file=/app/input/results.json touching file INFO 2026-01-21T15:11:01 +8ms service=bus type=message.part.updated publishing |  Write app/input/results.json INFO 2026-01-21T15:11:01 +5ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:11:01 +1ms service=bus type=message.updated publishing INFO 2026-01-21T15:11:01 +7ms service=bus type=message.updated publishing INFO 2026-01-21T15:11:01 +0ms service=bus type=session.status publishing INFO 2026-01-21T15:11:01 +1ms service=session.prompt step=2 sessionID=ses_41ee44c29ffemXANyVkM1ZprP3 loop INFO 2026-01-21T15:11:01 +27ms service=bus type=message.updated publishing INFO 2026-01-21T15:11:01 +1ms service=bus type=session.updated publishing INFO 2026-01-21T15:11:01 +2ms service=bus type=session.diff publishing INFO 2026-01-21T15:11:01 +3ms service=bus type=message.updated publishing INFO 2026-01-21T15:11:01 +0ms service=session.prompt status=started resolveTools INFO 2026-01-21T15:11:01 +2ms service=tool.registry status=started invalid INFO 2026-01-21T15:11:01 +1ms service=tool.registry status=started question INFO 2026-01-21T15:11:01 +0ms service=tool.registry status=started bash INFO 2026-01-21T15:11:01 +0ms service=bash-tool shell=/usr/bin/bash bash tool using shell INFO 2026-01-21T15:11:01 +1ms service=tool.registry status=started read INFO 2026-01-21T15:11:01 +0ms service=tool.registry status=started glob INFO 2026-01-21T15:11:01 +0ms service=tool.registry status=started grep INFO 2026-01-21T15:11:01 +0ms service=tool.registry status=started edit INFO 2026-01-21T15:11:01 +1ms service=tool.registry status=started write INFO 2026-01-21T15:11:01 +0ms service=tool.registry status=started task INFO 2026-01-21T15:11:01 +1ms service=tool.registry status=started webfetch INFO 2026-01-21T15:11:01 +0ms service=tool.registry 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ruleset=[{"permission":"*","action":"allow","pattern":"*"},{"permission":"doom_loop","action":"ask","pattern":"*"},{"permission":"external_directory","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","action":"deny","pattern":"*"},{"permission":"read","pattern":"*","action":"allow"},{"permission":"read","pattern":"*.env","action":"ask"},{"permission":"read","pattern":"*.env.*","action":"ask"},{"permission":"read","pattern":"*.env.example","action":"allow"},{"permission":"question","action":"allow","pattern":"*"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"}] evaluate INFO 2026-01-21T15:11:01 +0ms service=permission permission=task pattern=explore ruleset=[{"permission":"*","action":"allow","pattern":"*"},{"permission":"doom_loop","action":"ask","pattern":"*"},{"permission":"external_directory","pattern":"*","action":"ask"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"},{"permission":"question","action":"deny","pattern":"*"},{"permission":"read","pattern":"*","action":"allow"},{"permission":"read","pattern":"*.env","action":"ask"},{"permission":"read","pattern":"*.env.*","action":"ask"},{"permission":"read","pattern":"*.env.example","action":"allow"},{"permission":"question","action":"allow","pattern":"*"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output","action":"allow"},{"permission":"external_directory","pattern":"/home/cubbi/.local/share/opencode/tool-output/*","action":"allow"}] evaluate INFO 2026-01-21T15:11:01 +0ms service=tool.registry status=completed duration=6 task INFO 2026-01-21T15:11:01 +3ms service=session.prompt status=completed duration=14 resolveTools INFO 2026-01-21T15:11:01 +15ms service=session.processor process INFO 2026-01-21T15:11:01 +0ms service=llm providerID=openrouter modelID=google/gemini-2.5-flash-preview-09-2025 sessionID=ses_41ee44c29ffemXANyVkM1ZprP3 small=false agent=build stream INFO 2026-01-21T15:11:01 +8ms service=bus type=session.status publishing INFO 2026-01-21T15:11:02 +810ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:11:02 +1ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:11:02 +135ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:11:02 +74ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:11:02 +43ms service=bus type=message.part.updated publishing The relationship classifications have been completed based on the provided guidelines and test cases. The results have been written to `results.json`. INFO 2026-01-21T15:11:02 +5ms service=bus type=message.part.updated publishing INFO 2026-01-21T15:11:02 +1ms service=bus type=message.updated publishing INFO 2026-01-21T15:11:02 +30ms service=bus type=message.updated publishing INFO 2026-01-21T15:11:02 +0ms service=bus type=session.status publishing INFO 2026-01-21T15:11:02 +0ms service=session.prompt step=3 sessionID=ses_41ee44c29ffemXANyVkM1ZprP3 loop INFO 2026-01-21T15:11:02 +30ms service=bus type=message.updated publishing INFO 2026-01-21T15:11:02 +1ms service=bus type=session.updated publishing INFO 2026-01-21T15:11:02 +1ms service=bus type=session.diff publishing INFO 2026-01-21T15:11:02 +18ms service=session.prompt sessionID=ses_41ee44c29ffemXANyVkM1ZprP3 exiting loop INFO 2026-01-21T15:11:02 +1ms service=session.compaction pruning INFO 2026-01-21T15:11:02 +13ms service=session.prompt sessionID=ses_41ee44c29ffemXANyVkM1ZprP3 cancel INFO 2026-01-21T15:11:02 +0ms service=bus type=session.status publishing INFO 2026-01-21T15:11:02 +0ms service=bus type=session.idle publishing INFO 2026-01-21T15:11:02 +1ms service=default directory=/app/input disposing instance INFO 2026-01-21T15:11:02 +1ms service=state key=/app/input waiting for state disposal to complete INFO 2026-01-21T15:11:02 +2ms service=state key=/app/input state disposal completed --- Initial command finished (exit code: 0) --- --- no_shell=true, exiting container without starting shell --- Command execution complete. Container has exited. Session has been cleaned up.