Repair Windows staging and public skill discovery

.gitattributes

@@ -0,0 +1,3 @@
+tools/refresh_embedded_skill.py text eol=lf
+adapters/refresh_embedded_skill.py text eol=lf
+skills/selective-intelligence/evals/model-runs/*.json text eol=lf

README.md

@@ -4,7 +4,7 @@ Selective Intelligence—formerly Selective Inheritance—is a free, open-source
 
 **[Install Selective Intelligence from the public Plugins Directory](https://chatgpt.com/plugins/plugins_6a89b55ab8e88191addc1c063e779ca7?q=Selective+Intelligence)** · [Try five real pass/fail tasks](https://infotradescout.github.io/Selective-Intelligence/try/) · [Share the ready launch copy](LAUNCH.md)
 
-Published by [Platynum-47](https://github.com/Platynum-Standard). The canonical source is [infotradescout/Selective-Intelligence](https://github.com/infotradescout/Selective-Intelligence).
+Published by [Platynum-47](https://github.com/infotradescout). The canonical source is [infotradescout/Selective-Intelligence](https://github.com/infotradescout/Selective-Intelligence).
 
 > **Platynum-47 is a separate companion project in development.** It is being built as a phone-friendly workspace for non-developers. Its unfinished source remains private for now; Selective Intelligence stays independent, public, free, and usable without it.
 
@@ -28,13 +28,13 @@ The exact wordmark, any unmistakable request for a named Selective Intelligence
 
 After a direct trigger or that explicit yes, Selective Intelligence stays active for the entire task. The person can explicitly change or cancel the wanted outcome, but an accidental instruction to skip the checks cannot silently disable the intent, reuse, safety, token, correction, or proof gates.
 
-Token efficiency is the first operating priority. Selective Intelligence now defaults to one context, zero extra references before useful action, no Council, and no intent checkpoint for clear reversible work. It selects only context that can change the next decision, reuses existing owners, and reports results without repeated plans or filler. It never saves tokens by shrinking the wanted result or dropping proof.
+Token efficiency is the first operating priority. Selective Intelligence defaults to one bounded workflow with standing Orchestrator, Worker/Builder, and Objector responsibilities: understand intent, challenge a consequential misreading before work, execute, and check the result. Material project work uses separate contexts when available; clear reversible work keeps the check lightweight. Extra references and a formal Council are selected only when needed. It reuses existing owners and never saves tokens by shrinking the wanted result or dropping proof.
 
-An AI that can read ordinary text but cannot load Agent Skills should use [AI-GUIDE.md](skills/selective-intelligence/AI-GUIDE.md) as the strict operating guide after any direct match or approved merely adjacent adoption. It must perform the task rather than merely defining Selective Intelligence or summarizing this repository. [JUMPSTART.md](skills/selective-intelligence/JUMPSTART.md) remains the complete intentional-upload fallback; its multi-role workflow runs only for an explicit Council request or a documented high-consequence trigger.
+An AI that can read ordinary text but cannot load Agent Skills should use [AI-GUIDE.md](skills/selective-intelligence/AI-GUIDE.md) as the strict operating guide after any direct match or approved merely adjacent adoption. It must perform the task rather than merely defining Selective Intelligence or summarizing this repository. [JUMPSTART.md](skills/selective-intelligence/JUMPSTART.md) remains the complete intentional-upload fallback and carries the same standing Orchestrator, Worker/Builder, and Objector order; its additional formal Council roles are conditional.
 
 An AI with neither public-web access, installed-skill discovery, file input, nor supplied-text access cannot fetch any external guide from a name alone. It must say which capability is unavailable without inventing an installation, pretending it loaded the guide, or transferring technical setup to the person.
 
-Agent spawning is never a trigger by itself. For exceptional Council work, use the minimum selected roles—normally a Worker and one independent reviewer—and fall back to sequential contexts when spawning is unavailable. Another AI subscription is optional.
+Agent spawning is never a trigger by itself. For material project work, use separate contexts for the standing roles when available; otherwise label the same-context check as degraded. For exceptional Council work, add only the roles the case needs. Another AI subscription is optional.
 
 Along the way, save an approved durable decision, reusable output, or hard-won correction as a Project source so later chats inherit the understanding. Before saving, check ownership and permission to retain it, whether the Project is shared, what data is permitted, and the applicable data-use setting. Do not save secrets, brainstorming, stale prices, false completion claims, or cross-project material.
 
@@ -55,7 +55,7 @@ Use it when you want an agent to:
 
 - understand terse, corrective, or evolving intent without turning criticism into a new task or invented halt;
 - bridge a non-developer's product direction into exact journeys, design, architecture, implementation, operations, and proof without technical homework;
-- match effort to consequence: keep clear reversible work Lean even when durable, then add a bounded reviewer or full Council only for broad drift, ambiguity, money, security, sensitive data, destructive operations, or consequential release;
+- match effort to consequence: keep clear reversible work Lean with standing intent and result checks, and add formal Council controls for broad drift, ambiguity, money, security, sensitive data, destructive operations, or consequential release;
 - define a new product, smallest complete MVP, architecture, data, APIs, UI/UX, build order, and proof before coding;
 - resume a project across models, agents, branches, or interrupted sessions without losing the governing truth;
 - crawl a repository and reconcile intended behavior with routes, components, services, schemas, permissions, tests, deployment, and live surfaces;
@@ -95,9 +95,9 @@ Example requests:
 - “Pick this project back up from its current lock without repeating work or trusting stale evidence.”
 - “Use Selective Intelligence to audit and improve Selective Intelligence.”
 
-### Optional Council roles
+### Standing roles and optional Council helpers
 
-Non-developers do not need to run a seven-pass workflow. Ordinary work stays in one AI context. When consequence or an explicit request justifies Council, start with `si-worker` and one independent `si-objector` or `si-verifier`. Use `si-intake` for unresolved competing interpretations, `si-aligner` only when findings conflict, `si-queue-manager` only for a real queue, and a reserve context only for continuity or capacity risk.
+Non-developers do not need to manage agents. Orchestrator recovers intent; Objector checks it before Worker/Builder executes bounded work, then reviews the result and proof before final claims. Material projects use separate contexts when available; same-context checks are degraded, never independent. Use `si-intake` for unresolved competing Council interpretations, `si-aligner` only when findings conflict, `si-queue-manager` only for a real queue, and a reserve context only for continuity or capacity risk.
 
 ## Keep queued prompts from getting lost
 
@@ -111,7 +111,7 @@ This keeps context from drifting when users are spamming requests.
 
 ## Portable installation
 
-The canonical portable source is the complete [`skills/selective-intelligence/`](https://github.com/infotradescout/Selective-Intelligence/tree/main/skills/selective-intelligence) directory. Keep that directory intact: `SKILL.md`, `agents/`, `references/`, `schemas/`, `scripts/`, `metadata/`, `evals/`, `lanes/`, `subskills/`, and `tests/` form one skill.
+The canonical portable source is the complete [`skills/selective-intelligence/`](https://github.com/infotradescout/Selective-Intelligence/tree/main/skills/selective-intelligence) directory. Versioned archives and checksums are pending publication; [view release status](https://github.com/infotradescout/Selective-Intelligence/releases). Use the canonical source directory for portable installation and keep it intact: `SKILL.md`, `agents/`, `references/`, `schemas/`, `scripts/`, `metadata/`, `evals/`, `lanes/`, `subskills/`, and `tests/` form one skill.
 
 Client adapters are generated from that portable source and may change only packaging, never the behavioral contract. The supported ChatGPT adapter is rebuilt and tested with [`tools/build_chatgpt_adapter.py`](tools/build_chatgpt_adapter.py) and [`tools/test_chatgpt_adapter.py`](tools/test_chatgpt_adapter.py).
 
@@ -136,15 +136,17 @@ Common project-level destinations are:
 
 Use the canonical repository or versioned release archive as the source for every destination. Client paths are adapters, not separate editions.
 
-Filesystem access is required for repository and Start modes. Python 3.10 or newer runs the dependency-free validators. Live web evidence needs browser or network access. When a capability is unavailable, the skill narrows the blocker and preserves the same truth standard.
+Filesystem access is required for repository and Start modes. Python 3.11 or newer runs the dependency-free validators. Live web evidence needs browser or network access. When a capability is unavailable, the skill narrows the blocker and preserves the same truth standard.
 
 The current v1 evidence is recorded in [evals/results-1.0.5.json](skills/selective-intelligence/evals/results-1.0.5.json). Deterministic controls and production-path tests pass locally, and public directory publication is verified. The complete hidden-oracle behavior suite, outside-account installation, real-task outcomes, and genuine free-tier portability gate remain open until fresh evidence satisfies them. Cross-client equivalence is not claimed without execution proof.
 
 ### Update and uninstall
 
-To update after publication, run `gh skill update selective-intelligence`, or obtain a newer versioned archive or canonical repository revision, verify its release checksum, and replace only the existing `selective-intelligence` skill directory at the destination you chose. Preserve any project-created `.selective-intelligence/` Start Packs and feedback stores; they are project data, not installed skill files.
+To update after publication, obtain a newer published versioned archive and verify its release checksum, or select an explicit canonical repository revision. If your existing GitHub CLI supports `gh skill`, you can instead run `gh skill update selective-intelligence`; a CLI upgrade is not required for the archive or source route. Replace only the existing `selective-intelligence` skill directory at the destination you chose, preserving local changes and any project-created `.selective-intelligence/` Start Packs and feedback stores. Those stores are project data, not installed skill files.
 
-Version 1.0.5 keeps the 1.0.4 uploader corrections, cuts the always-loaded master instructions by a further 38.51%, and separates runtime files from repository-only development evidence. Public and personal bundles now stay below 55 files and exclude tests, historical results, release machinery, READMEs, and changelogs.
+For maintainers updating the public listing, first satisfy the candidate's proof gates, then open the existing Selective Intelligence plugin in [OpenAI Platform Plugins](https://platform.openai.com/plugins) under its existing publisher account. Upload the complete skills-only plugin ZIP, inspect Metadata & Skills and automated findings, complete the applicable review, and publish the approved package version. A GitHub push does not update the published skill. Use the [existing-plugin update instructions](https://developers.openai.com/plugins/deploy/submission#update-your-published-plugin); do not create a replacement plugin or new service to update the current listing.
+
+Public and personal runtime bundles contain one `SKILL.md` and seven role references. They exclude tests, historical results, release machinery, READMEs, and changelogs; the full portable archive retains the complete source and proof. The personal runtime limit remains 59 files, and the public limit remains 61 entries including its manifest and icon. Both retain the 1 MiB uncompressed runtime budget.
 
 To uninstall, remove only the installed `selective-intelligence` skill directory from that documented destination. Do not delete a parent skills directory or any project `.selective-intelligence/` directory.