chore(release): v4.12.1

.gemini/skills-index.json

@@ -1,6 +1,6 @@
 {
   "version": "1.0.0",
-  "updated": "2026-09-21T22:03:54+00:00",
+  "updated": "2026-09-27T19:16:28+00:00",
   "total_skills": 372,
   "skills": [
     {
@@ -266,7 +266,7 @@
     },
     {
       "name": "claude-code-mastery",
-      "description": "",
+      "description": ">-",
       "domain": "engineering",
       "path": "engineering/claude-code-mastery/SKILL.md",
       "tools": [
@@ -1033,7 +1033,7 @@
     },
     {
       "name": "senior-cloud-architect",
-      "description": "",
+      "description": ">-",
       "domain": "engineering",
       "path": "engineering/senior-cloud-architect/SKILL.md",
       "tools": [],
@@ -1084,7 +1084,7 @@
     },
     {
       "name": "senior-data-scientist",
-      "description": "",
+      "description": ">-",
       "domain": "engineering",
       "path": "engineering/senior-data-scientist/SKILL.md",
       "tools": [
@@ -1173,7 +1173,7 @@
     },
     {
       "name": "senior-mobile",
-      "description": "",
+      "description": ">-",
       "domain": "engineering",
       "path": "engineering/senior-mobile/SKILL.md",
       "tools": [

CHANGELOG.md

@@ -5,6 +5,19 @@ All notable changes to the Claude Skills Library will be documented in this file
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [4.12.1] - 2026-09-27 (current-Claude accuracy pass)
+
+### Fixed
+
+- **Four skills could not be routed to.** The frontmatter standardisation left `description` empty on `claude-code-mastery`, `senior-mobile`, `senior-data-scientist` and `senior-cloud-architect`; each description is restored.
+- **`claude-code-mastery` teaches the real subagent format**: a Markdown file in `.claude/agents/` with `name`, `description`, `tools` and `model` in the frontmatter and the system prompt as the body. The `.yaml` files, `allowed-tools:` and `custom-instructions:` it showed are ignored by Claude Code, so agents built from them got every tool and no prompt.
+- **Retired and never-valid Claude model IDs are gone from examples, templates and cost tools** (`claude-3-opus-20240229`, `claude-haiku-4-20250514`, `claude-haiku-3-5-20241022`, …). API examples use `claude-sonnet-5`, `claude-opus-5` and `claude-haiku-4-5`; agent files use the `sonnet` / `opus` / `haiku` aliases. The cost tools are re-priced (Sonnet 5 $2/$10, Haiku 4.5 $1/$5, Opus 5 $5/$25, Opus 5.5 $4/$20, Fable 5.1 $10/$50) and keep the legacy dated IDs at their old prices so older workflow files still cost correctly.
+
+### Changed
+
+- **Prompting guides carry current-Claude notes** next to "think step by step", scratchpad tags, `CRITICAL:` prefixes and temperature tuning: on current Claude models thinking depth is set with `effort`, asking for reasoning in the output can be refused, emphasis over-triggers, and structured outputs replace JSON-by-instruction. The techniques stay for other providers.
+- CLAUDE.md no longer describes a finished November 2025 sprint as active.
+
 ## [4.12.0] - 2026-09-22 (2026 refresh — AI-era marketing and PM, security hardening)
 
 **372 skills · 20 domains · 867 Python tools.**

CLAUDE.md

@@ -39,8 +39,6 @@ This repository uses **modular documentation**. For domain-specific guidance, se
 | **Standards Library** | [standards/CLAUDE.md](standards/CLAUDE.md) | Communication, quality, git, security standards |
 | **Templates** | [templates/CLAUDE.md](templates/CLAUDE.md) | Template system usage |
 
-**Current Sprint:** See [documentation/delivery/sprint-11-05-2025/](documentation/delivery/sprint-11-05-2025/) for active sprint context and progress.
-
 ## Architecture Overview
 
 ### Repository Structure
@@ -181,23 +179,6 @@ hand-maintained `site/index.html`.
 - Document all dependencies in SKILL.md
 - Prefer standard library implementations
 
-## Current Sprint
-
-**Active Sprint:** sprint-11-05-2025 (Nov 5-19, 2025)
-**Goal:** Skill-Agent Integration Phase 1-2
-**Status:** ✅ COMPLETE - All 6 days finished, 5 agents deployed
-
-**Deliverables:**
-- 5 production agents: cs-content-creator, cs-demand-gen-specialist, cs-ceo-advisor, cs-cto-advisor, cs-product-manager
-- 1 agent template for future development
-- Modular documentation structure (main + 9 domain CLAUDE.md files)
-- Branch protection and workflow documentation
-
-**Progress Tracking:**
-- [Sprint Plan](documentation/delivery/sprint-11-05-2025/plan.md) - Day-by-day execution plan
-- [Sprint Context](documentation/delivery/sprint-11-05-2025/context.md) - Goals, scope, risks
-- [Sprint Progress](documentation/delivery/sprint-11-05-2025/PROGRESS.md) - Real-time auto-updating tracker
-
 ## Roadmap
 
 **Phase 1-4 Complete:** 245 production-ready skills deployed
@@ -250,7 +231,7 @@ hand-maintained `site/index.html`.
 ---
 
 **Last Updated:** September 2026
-**Version:** 4.12.0
+**Version:** 4.12.1
 **Status:** 372 skills, 68 cs-* agents (+ 8 personas), 26 commands, 21 sub-skills, 20 domains (incl. workflow meta-skills), Gemini CLI support. Engineering domain adds 4 AI-modernization skills (extended-thinking-architect, batch-api-orchestrator, computer-use-automation, agentic-evaluation-framework) + memory-tool/context-editing/reasoning-effort/caching upgrades to context-engine, llm-cost-optimizer, agent-workflow-designer, mcp-server-builder. Cross-platform surface unified — one `build_manifest.py` run regenerates `cli/skills.json`, `registry.json`, `.gemini/skills-index.json`, and the website catalog `skills.json`; all 20 domains install as Claude Code plugins; Cursor `.cursor/rules/*.mdc` added. PM domain expanded to 70 skills with career track, AI/ML PRD, activation funnels, feature flags, post-mortems, customer feedback triage, pricing PRDs, Linear/Notion/Productboard integrations, strategy frameworks (BMC/lean/SWOT/Porter's/Ansoff), and GTM (gtm-strategy/ICP).
 - **Recent additions (September 2026) — 4 skills + 2026 refresh:** marketing `ai-content-disclosure` and `conversational-ads`; PM `discovery/ai-prototyping` and `execution/agents-in-the-team` (8 stdlib tools). Existing marketing and PM skills refreshed against 2025–2026 changes: retired FAQ/HowTo rich results, AI crawler and Search Console AI controls, Advantage+/AI Max, GA4 AI Assistant channel, Productboard API v2, Jira `/search/jql`, Notion data sources, DORA 2024 benchmarks, EU AI Act Omnibus (Reg. 2026/1744), Atlassian Data Center end-of-life. Workflow templates hardened against shell injection (CWE-78).
 - **Recent additions (July 2026) — 25 skills, 3 new domains:** `business-operations/` (capacity-planner, process-mapper, vendor-management, internal-comms, knowledge-ops, procurement-optimizer), `research-ops/` (market-research, product-research, clinical-research, research-finance — applied/operational, distinct from academic `research/`), and `markdown-html/` (md-document, md-slides, md-review, design-system — stdlib-only markdown→HTML with zero network calls). Plus 5 engineering skills (write-a-skill, spec-driven-workflow, code-tour, agent-harness, cloud-security), data-analytics/statistical-analyst, 2 PM skills (team-communications, meeting-analyzer), and 3 personal-productivity skills (capture, deep-work, reflect). 44 new stdlib Python tools. Several tools ship deliberate CI gates that exit non-zero on flawed sample data — see each SKILL.md's exit-code contract.

cli/skills.json

@@ -1,6 +1,6 @@
 {
   "schema_version": "1.0.0",
-  "generated_at": "2026-09-21T22:03:54+00:00",
+  "generated_at": "2026-09-27T19:16:28+00:00",
   "skill_count": 372,
   "domain_count": 20,
   "skills": [
@@ -65,7 +65,7 @@
         "references/troubleshooting-and-tool-reference.md",
         "tool_schema_generator.py"
       ],
-      "size_bytes": 288146,
+      "size_bytes": 288239,
       "tools_count": 0,
       "has_scripts": false,
       "has_references": true,
@@ -160,7 +160,7 @@
         "scripts/workflow_validator.py",
         "scripts/workflow_visualizer.py"
       ],
-      "size_bytes": 96002,
+      "size_bytes": 96444,
       "tools_count": 4,
       "has_scripts": true,
       "has_references": true,
@@ -552,7 +552,7 @@
     {
       "name": "claude-code-mastery",
       "domain": "engineering",
-      "description": "",
+      "description": ">-",
       "tags": [
         "claude-code",
         "skill-authoring",
@@ -580,7 +580,7 @@
         "scripts/context_analyzer.py",
         "scripts/skill_scaffolder.py"
       ],
-      "size_bytes": 128126,
+      "size_bytes": 130993,
       "tools_count": 3,
       "has_scripts": true,
       "has_references": true,
@@ -1146,7 +1146,7 @@
         "scripts/reasoning_budget_advisor.py",
         "scripts/reasoning_loop_allocator.py"
       ],
-      "size_bytes": 38865,
+      "size_bytes": 39060,
       "tools_count": 2,
       "has_scripts": true,
       "has_references": true,
@@ -1501,7 +1501,7 @@
         "scripts/prompt_optimizer.py",
         "scripts/token_counter.py"
       ],
-      "size_bytes": 50428,
+      "size_bytes": 50736,
       "tools_count": 3,
       "has_scripts": true,
       "has_references": true,
@@ -1800,7 +1800,7 @@
         "scripts/prompt_analyzer.py",
         "scripts/prompt_diff.py"
       ],
-      "size_bytes": 59814,
+      "size_bytes": 60506,
       "tools_count": 3,
       "has_scripts": true,
       "has_references": true,
@@ -2203,7 +2203,7 @@
     {
       "name": "senior-cloud-architect",
       "domain": "engineering",
-      "description": "",
+      "description": ">-",
       "tags": [
         "cloud",
         "aws",
@@ -2225,7 +2225,7 @@
         "references/cloud-architecture-playbooks.md",
         "references/cloud-operations.md"
       ],
-      "size_bytes": 14267,
+      "size_bytes": 14721,
       "tools_count": 0,
       "has_scripts": false,
       "has_references": true,
@@ -2304,7 +2304,7 @@
     {
       "name": "senior-data-scientist",
       "domain": "engineering",
-      "description": "",
+      "description": ">-",
       "tags": [
         "data-science",
         "ml",
@@ -2331,7 +2331,7 @@
         "scripts/feature_engineering_pipeline.py",
         "scripts/model_evaluation_suite.py"
       ],
-      "size_bytes": 32079,
+      "size_bytes": 32553,
       "tools_count": 3,
       "has_scripts": true,
       "has_references": true,
@@ -2469,7 +2469,7 @@
         "scripts/model_deployment_pipeline.py",
         "scripts/rag_system_builder.py"
       ],
-      "size_bytes": 53376,
+      "size_bytes": 53433,
       "tools_count": 3,
       "has_scripts": true,
       "has_references": true,
@@ -2478,7 +2478,7 @@
     {
       "name": "senior-mobile",
       "domain": "engineering",
-      "description": "",
+      "description": ">-",
       "tags": [
         "mobile",
         "ios",
@@ -2508,7 +2508,7 @@
         "scripts/mobile_scaffold.py",
         "scripts/store_metadata_generator.py"
       ],
-      "size_bytes": 197086,
+      "size_bytes": 197539,
       "tools_count": 3,
       "has_scripts": true,
       "has_references": true,
@@ -2541,7 +2541,7 @@
         "scripts/prompt_optimizer.py",
         "scripts/rag_evaluator.py"
       ],
-      "size_bytes": 132477,
+      "size_bytes": 133091,
       "tools_count": 3,
       "has_scripts": true,
       "has_references": true,

docs/INSTALLATION.md

@@ -963,5 +963,5 @@ See `.codex/skills-index.json` for the complete manifest with descriptions.
 ---
 
 **Last Updated:** September 2026
-**Skills Version:** 4.12.0 (372 production skills, 867 Python tools, 76 agents, 26 slash commands, 21 compound sub-skills, 8 CI/CD workflows)
+**Skills Version:** 4.12.1 (372 production skills, 867 Python tools, 76 agents, 26 slash commands, 21 compound sub-skills, 8 CI/CD workflows)
 **Universal Installer:** [Agent Skills CLI](https://github.com/Karanjot786/agent-skills-cli)

docs/changelog.md

@@ -8,7 +8,9 @@ For the complete version history and release notes, see [CHANGELOG.md](https://g
 
 ## Current Version
 
-**v4.12.0** (September 2026)
+**v4.12.1** (September 2026)
+
+- Current-Claude accuracy pass: four skill descriptions restored, the real Claude Code subagent format in `claude-code-mastery`, current model IDs and prices in every example and cost tool
 
 - 372 production-ready skills across 20 domains, 867 Python automation tools, 76 agents
 - 4 new AI-era skills: `ai-content-disclosure` and `conversational-ads` (marketing), `ai-prototyping` and `agents-in-the-team` (project management)

documentation/WORKFLOW.md

@@ -127,8 +127,8 @@ There is no `dev → main` release PR. A release is simply an annotated tag on `
 
 ```bash
 git checkout main && git pull origin main
-git tag -a v4.12.0 -m "v4.12.0 — <summary>"
-git push origin v4.12.0
+git tag -a v4.12.1 -m "v4.12.1 — <summary>"
+git push origin v4.12.1
 ```
 
 (`cli-v*` tags trigger the npm publish workflow; `vX.Y.Z` tags do not.)

engineering/agent-designer/README.md

@@ -377,7 +377,8 @@ with open('my_tools_anthropic.json') as f:
 # Use with Anthropic tool use
 client = anthropic.Anthropic()
 response = client.messages.create(
-    model="claude-3-opus-20240229",
+    model="claude-opus-5",
+    max_tokens=16000,
     messages=[{"role": "user", "content": "Search for AI news"}],
     tools=schemas['tools']
 )

engineering/agent-designer/agent_evaluator.py

@@ -223,7 +223,8 @@ def _define_cost_benchmarks(self) -> Dict[str, Any]:
             "token_costs": {
                 "gpt-4": {"input": 0.00003, "output": 0.00006},
                 "gpt-3.5-turbo": {"input": 0.000002, "output": 0.000002},
-                "claude-3": {"input": 0.000015, "output": 0.000075}
+                "claude-opus-5": {"input": 0.000005, "output": 0.000025},
+                "claude-sonnet-5": {"input": 0.000002, "output": 0.00001}
             },
             "operation_costs": {
                 "simple_task": 0.005,

engineering/agent-workflow-designer/references/orchestration-patterns.md

@@ -22,7 +22,7 @@ class PipelineState(TypedDict):
     stage_costs: Annotated[list[dict], "append"]  # accumulates cost per stage
 
 def research_stage(state: PipelineState) -> dict:
-    model = ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=2048)
+    model = ChatAnthropic(model="claude-sonnet-5", max_tokens=2048)
     result = model.invoke(
         f"Research the following topic thoroughly. Provide key facts, statistics, "
         f"and expert perspectives:\n\n{state['topic']}"
@@ -33,7 +33,7 @@ def research_stage(state: PipelineState) -> dict:
     }
 
 def writing_stage(state: PipelineState) -> dict:
-    model = ChatAnthropic(model="claude-sonnet-4-20250514", max_tokens=4096)
+    model = ChatAnthropic(model="claude-sonnet-5", max_tokens=4096)
     result = model.invoke(
         f"Using this research, write a compelling 800-word blog post with a hook, "
         f"3 main sections, and a CTA:\n\n{state['research']}"
@@ -44,7 +44,7 @@ def writing_stage(state: PipelineState) -> dict:
     }
 
 def editing_stage(state: PipelineState) -> dict:
-    model = ChatAnthropic(model="claude-haiku-4-20250514", max_tokens=4096)
+    model = ChatAnthropic(model="claude-haiku-4-5", max_tokens=4096)
     result = model.invoke(
         f"Edit this draft for clarity, flow, and grammar. Return only the improved "
         f"version:\n\n{state['draft']}"
@@ -84,7 +84,7 @@ class FanOutTask:
     name: str
     system_prompt: str
     user_message: str
-    model: str = "claude-sonnet-4-20250514"
+    model: str = "claude-sonnet-5"
 
 @dataclass
 class FanOutResult:
@@ -144,7 +144,7 @@ async def fan_out_fan_in(
     )
 
     merge_response = await client.messages.create(
-        model="claude-sonnet-4-20250514",
+        model="claude-sonnet-5",
         max_tokens=4096,
         system="Synthesize the following parallel analyses into a unified report.",
         messages=[{"role": "user", "content": f"{merge_prompt}\n\n{combined}"}],
@@ -188,7 +188,7 @@ class HierarchicalOrchestrator:
     async def plan(self, request: str) -> list[SubTask]:
         """Orchestrator creates an execution plan with dependencies."""
         response = await self.client.messages.create(
-            model="claude-sonnet-4-20250514",
+            model="claude-sonnet-5",
             max_tokens=2048,
             system=f"""You are a task orchestrator. Break down the request into subtasks.
 Available specialists: {', '.join(SPECIALISTS.keys())}
@@ -219,7 +219,7 @@ Rules:
         # Final synthesis
         all_outputs = "\n\n".join(f"### {k}\n{v}" for k, v in results.items())
         synthesis = await self.client.messages.create(
-            model="claude-sonnet-4-20250514",
+            model="claude-sonnet-5",
             max_tokens=4096,
             system="Synthesize specialist outputs into a coherent final response.",
             messages=[{"role": "user", "content": f"Request: {request}\n\nOutputs:\n{all_outputs}"}],

engineering/agent-workflow-designer/references/routing-and-cost.md

@@ -11,18 +11,18 @@ class IntentRouter:
     """Route requests to specialized agents based on intent classification."""
 
     ROUTING_TABLE = {
-        "code_generation": {"agent": "coder", "model": "claude-sonnet-4-20250514"},
-        "code_review": {"agent": "reviewer", "model": "claude-sonnet-4-20250514"},
-        "research": {"agent": "researcher", "model": "claude-sonnet-4-20250514"},
-        "simple_question": {"agent": "assistant", "model": "claude-haiku-4-20250514"},
-        "creative_writing": {"agent": "writer", "model": "claude-sonnet-4-20250514"},
-        "complex_analysis": {"agent": "analyst", "model": "claude-sonnet-4-20250514"},
+        "code_generation": {"agent": "coder", "model": "claude-sonnet-5"},
+        "code_review": {"agent": "reviewer", "model": "claude-sonnet-5"},
+        "research": {"agent": "researcher", "model": "claude-sonnet-5"},
+        "simple_question": {"agent": "assistant", "model": "claude-haiku-4-5"},
+        "creative_writing": {"agent": "writer", "model": "claude-sonnet-5"},
+        "complex_analysis": {"agent": "analyst", "model": "claude-sonnet-5"},
     }
 
     async def route(self, message: str) -> dict:
         # Use a fast, cheap model for classification
         classification = await self.client.messages.create(
-            model="claude-haiku-4-20250514",
+            model="claude-haiku-4-5",
             max_tokens=50,
             system="Classify the user intent. Respond with ONLY one of: code_generation, code_review, research, simple_question, creative_writing, complex_analysis",
             messages=[{"role": "user", "content": message}],
@@ -35,9 +35,9 @@ class IntentRouter:
 
 ```python
 MODEL_LIMITS = {
-    "claude-sonnet-4-20250514": 200_000,
-    "claude-haiku-4-20250514": 200_000,
-    "claude-opus-4-20250514": 200_000,
+    "claude-sonnet-5": 1_000_000,
+    "claude-haiku-4-5": 200_000,
+    "claude-opus-5": 1_000_000,
     "gpt-4o": 128_000,
 }