{"id":16792,"plugin_id":"plugins_6a57b17fb5848191be710192d93fe03a","kind":"skill","collection_source":null,"comparison_source":null,"observed_at":"2026-09-30T23:13:47.145Z","digest":"0f37a4b0829233c5118e5e1f867f6c1d034315213805a45145f3d00867e5b2f3","against":null,"payload":{"description":"Use when a user wants Clara to map retail product attributes, preserve the existing new-versus-rest or best-seller-versus-other analysis, create a private local HTML report, or answer whether that report is correct.","included_files":[{"relative_path":"agents/openai.yaml","size_in_bytes":322}],"name":"attribute-reporting","skill_md_contents":"---\nname: attribute-reporting\ndescription: Use when a user wants Clara to map retail product attributes, preserve the existing new-versus-rest or best-seller-versus-other analysis, create a private local HTML report, or answer whether that report is correct.\n---\n\n<!-- CLARA_OPENAI_ONBOARDING_BEGIN -->\nOnboarding is optional. Continue ordinary professional work immediately,\nincluding direct specialist invocation, without checking or completing a local\nonboarding profile. Missing, unfinished, inaccessible or corrupt onboarding state,\nor unavailable voice/window controls, must never block ordinary work. Do not\nautomatically start, resume or repeatedly offer onboarding.\nOnly for a user-requested tutorial or a native teaching handoff, read\n`../clara/references/local-onboarding.md`. A verified paired lesson worker\nexecutes only its bound lesson and token; never bypass tutorial validation.\nTutorial profiles, progress, examples and feedback remain local; never send a\nchange request, stamp a tutorial receipt or call hosted interviews for a tutorial.\nCurrent user requests take precedence over saved preferences.\n<!-- CLARA_OPENAI_ONBOARDING_END -->\n\n# Attribute Reporting\n\nAfter substantive use of this workflow, read and follow the `Plugin Improvement Feedback` section in `../clara/SKILL.md`.\n\nResolve `../../modules/attribute-reporting` from this skill directory when it\nexists; otherwise resolve `../../../attribute-reporting` in the repository.\nRead that component's `skills/attribute-reporting/SKILL.md` completely and\nfollow it. Treat the resolved component root as a read-only execution root for\nits scripts, requirements, references, and vendored modules. Run component\nhelpers with that root as the working directory, but create every user run and\nartifact outside the resolved component root, every Git repository, and every\nplugin cache. Never place run artifacts in the packaged component.\n\nBefore running component helper scripts, delegate the dependency check from\nthe Clara root:\n\n```bash\npython scripts/check_dependencies.py --module attribute-reporting\n```\n\nAttribute Reporting is a self-contained analytical workflow. Do not register\nits report in an advisory case, convert it into a 16:9 presentation, or upload\nit to Mparanza unless the user separately asks for that follow-on work. If the\nuser asks for a presentation after the checked HTML report is complete, hand\nthe finished report to Clara's `html-deck` workflow as a new, explicit step.\n\nReport files and image bytes remain local. Mapping and report evidence that\nCodex reads may enter model context through the user's existing ChatGPT plan;\nthe component helper scripts make no separate model API call. The authenticated\nretail-data bridge remains a distinct Mparanza-hosted service.\n\nDo not use this workflow for Brand Fit. When the user wants to compare completed\nretailer signals with both a brand's current presence at that retailer and the\nbrand-owned catalogue, route to Clara's distinct `brand-fit` skill.\n"},"changes":[],"summary":"First saved snapshot. No earlier version is available for comparison.","summary_kind":"deterministic","summary_metadata":{}}