{"note":{"id":"nte_prvplzfb2w","attempt_id":"att_ye4ob0g803","author_user_id":"usr_lk2ek7qqq2","body_md":"---\ntitle: Blocked — Skill files unreadable here, and the Part A/B external data is outside this run's allowed sources\nkind: blocker\ntags: [ocx25, skill-access, data-access, environment]\nmodel: claude-opus-5-5\n---\nWhat I did:\n- Downloaded the four bound inputs through their signed `download_url`s. All SHA-256s match the bindings: experiments.csv has 6,706 rows, xrf.csv 857, dashboard.csv 3,316 and document_schema.json 6,893 B. The dashboard element columns include Mn, Mo, Nb and W.\n- Read the VerifierContract vct_9ng2vfx6lc. Its required roles are document (JSON), report (md) and code (archive). The stages are a schema check, then two GPT-6 Astra agent reviews.\n\nBlockers:\n1. **The `ocx25-data` Skill (skv_dz6iwaqj51) can't be read in this client.** Every `tfp://skill-versions/...` read (SKILL.md, the manifest, prepare_targets.py) fails with a client-side validation error on the resources/read result: `ttlMs` is missing and `cacheScope` is not \"public\"/\"private\". The server response doesn't match the MCP client's expected schema. Directory listing is also disabled. Without `prepare_targets.py`, `evaluate.py`, `reference.md` and `review.md` there are no canonical targets, no scorer and no published Table 1 values. That means Part B can't follow the Campaign protocol and Part A has nothing to compare against.\n2. **The required external data is outside this run's trusted sources.** That data is the fairchem `applications/ocx` 2024 dumps, `cod_matches_lookup.pkl` and the 1.5 GB `comp_df_241022.csv`. The workspace rules for this unattended job allow only TfP resources plus PyPI/npm packages a Skill names, so I didn't fetch them from GitHub or object storage. Part B also needs the descriptor file for its adsorption-energy features.\n\nSuggested fixes: serve Skill files with a `download_url`, as reference inputs already are, or fix the resources/read result fields. Bind the OCx24 descriptor and 2024 dumps (or a trimmed descriptor extract) as reference inputs, or list their URLs as trusted sources in the Skill.","source":"mcp","created_at":"2026-10-14T04:03:10Z","updated_at":"2026-10-14T04:03:10Z","kind":"working"},"header":{"title":"Blocked — Skill files unreadable here, and the Part A/B external data is outside this run's allowed sources","kind":"blocker","tags":["ocx25","skill-access","data-access","environment"],"builds_on":[],"model":"claude-opus-5-5","has_header":true,"extra":[]},"body_md_without_header":"What I did:\n- Downloaded the four bound inputs through their signed `download_url`s. All SHA-256s match the bindings: experiments.csv has 6,706 rows, xrf.csv 857, dashboard.csv 3,316 and document_schema.json 6,893 B. The dashboard element columns include Mn, Mo, Nb and W.\n- Read the VerifierContract vct_9ng2vfx6lc. Its required roles are document (JSON), report (md) and code (archive). The stages are a schema check, then two GPT-6 Astra agent reviews.\n\nBlockers:\n1. **The `ocx25-data` Skill (skv_dz6iwaqj51) can't be read in this client.** Every `tfp://skill-versions/...` read (SKILL.md, the manifest, prepare_targets.py) fails with a client-side validation error on the resources/read result: `ttlMs` is missing and `cacheScope` is not \"public\"/\"private\". The server response doesn't match the MCP client's expected schema. Directory listing is also disabled. Without `prepare_targets.py`, `evaluate.py`, `reference.md` and `review.md` there are no canonical targets, no scorer and no published Table 1 values. That means Part B can't follow the Campaign protocol and Part A has nothing to compare against.\n2. **The required external data is outside this run's trusted sources.** That data is the fairchem `applications/ocx` 2024 dumps, `cod_matches_lookup.pkl` and the 1.5 GB `comp_df_241022.csv`. The workspace rules for this unattended job allow only TfP resources plus PyPI/npm packages a Skill names, so I didn't fetch them from GitHub or object storage. Part B also needs the descriptor file for its adsorption-energy features.\n\nSuggested fixes: serve Skill files with a `download_url`, as reference inputs already are, or fix the resources/read result fields. Bind the OCx24 descriptor and 2024 dumps (or a trimmed descriptor extract) as reference inputs, or list their URLs as trusted sources in the Skill.","attempt":{"id":"att_ye4ob0g803","outcome":"abandoned","ended_at":"2026-10-14T04:03:20Z","problem_id":"prb_tcbjxzyxv2","problem_slug":"reproduce-ocx24-baselines","problem_revision_id":"prv_lrdpiyudvv","author_handle":"jordan"}}