Add Claude Code skills Memanto example

examples/claudecode-skills-memanto/.env.example

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+MOORCHEH_API_KEY=
+MEMANTO_SKILLS_AGENT_ID=claude-skills-memory
+MEMANTO_SKILLS_BACKEND=local
+MEMANTO_SKILLS_STORE=.memanto-skills-memory.json

examples/claudecode-skills-memanto/.gitignore

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+.tmp/
+__pycache__/
+*/__pycache__/
+validation-memory.json
+.memanto-skills-memory.json

examples/claudecode-skills-memanto/README.md

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+# Claude Code Skills + Memanto
+
+This example shows how to use Memanto as a shared engineering memory layer across Claude Code skill runs. It is built for workflows such as `/grill-with-docs`, `/tdd`, `/handoff`, and custom project skills where the same architectural decisions and project preferences need to survive across separate sessions.
+
+The bridge has two jobs:
+
+1. Before a skill starts, recall relevant project memories and print a compact context block that can be injected into the prompt.
+2. After a skill finishes, extract durable engineering facts from the request and result, then store them for future skill runs.
+
+The example works in two modes:
+
+- Local mode: deterministic JSON storage for validation, demos, and CI.
+- Live mode: optional Memanto/Moorcheh storage when `MOORCHEH_API_KEY` is present.
+
+## Why this solves the bounty
+
+The common failure mode in skill-based workflows is context fragmentation. A review skill may discover that a service must stay within the free tier, but a later implementation skill does not know that. This bridge preserves those decisions as reusable memory.
+
+It is intentionally small:
+
+- No changes to the main Memanto package are required.
+- The hook accepts JSON from stdin, so it can be wired into Claude Code hooks, shell wrappers, or other skill runners.
+- The recall step uses a strict character budget so the injected memory block stays concise.
+- The write step only stores durable engineering guidance, not raw transcripts or secrets.
+
+## Files
+
+```text
+examples/claudecode-skills-memanto/
+├── README.md
+├── .env.example
+├── settings.example.json
+├── validate_offline.py
+├── skill_memory_bridge/
+│   ├── __init__.py
+│   ├── bridge.py
+│   └── cli.py
+└── tests/
+    └── test_bridge.py
+```
+
+## Quick validation
+
+Run the offline proof from the repository root:
+
+```bash
+python examples/claudecode-skills-memanto/validate_offline.py
+```
+
+Expected output:
+
+```text
+offline validation passed
+```
+
+Run the focused tests:
+
+```bash
+python -m pytest examples/claudecode-skills-memanto/tests -q
+```
+
+## Claude Code hook setup
+
+Copy the example settings beside your Claude Code settings file, then merge the hook entries into your existing settings after adjusting paths for your machine:
+
+```bash
+cp examples/claudecode-skills-memanto/settings.example.json ~/.claude/settings.memanto.example.json
+```
+
+Do not overwrite an existing `~/.claude/settings.json` unless you have backed it up first.
+
+The important parts are:
+
+- `UserPromptSubmit` calls `cli.py pre` and injects recalled memory.
+- `Stop` calls `cli.py post` and stores durable decisions from the completed run.
+
+The hook reads JSON from stdin. If your runner uses a different event shape, keep the same fields when possible:
+
+```json
+{
+  "skill": "/tdd",
+  "project": "billing-api",
+  "file_path": "src/billing/routes.py",
+  "input": "Add invoice retry tests.",
+  "output": "Implemented tests. Keep Stripe calls mocked in unit tests."
+}
+```
+
+## Live Memanto mode
+
+Local mode is the default. To use the Memanto backend, create a free Moorcheh API key and set:
+
+```bash
+export MOORCHEH_API_KEY="..."
+export MEMANTO_SKILLS_AGENT_ID="claude-skills-memory"
+export MEMANTO_SKILLS_BACKEND="memanto"
+```
+
+When live mode is enabled, the bridge stores memories through the Memanto Python package. If the live backend is unavailable, the CLI exits with a clear error instead of silently dropping memory.
+
+## Demo transcript
+
+First skill run stores architectural guidance:
+
+```bash
+printf '%s' '{
+  "skill": "/grill-with-docs",
+  "project": "support-api",
+  "file_path": "src/support/router.py",
+  "input": "Review the API design.",
+  "output": "Decision: keep FastAPI endpoints async. Preference: do not add paid services. Constraint: redact customer emails in logs."
+}' | python examples/claudecode-skills-memanto/skill_memory_bridge/cli.py post
+```
+
+Later, a different skill receives the relevant context:
+
+```bash
+printf '%s' '{
+  "skill": "/tdd",
+  "project": "support-api",
+  "file_path": "src/support/tests/test_router.py",
+  "input": "Write tests for the support ticket route."
+}' | python examples/claudecode-skills-memanto/skill_memory_bridge/cli.py pre
+```
+
+Example injected block:
+
+```text
+<memanto_memory_context>
+- Keep FastAPI endpoints async.
+- Do not add paid services.
+- Redact customer emails in logs.
+</memanto_memory_context>
+```
+
+## Safety behavior
+
+The extractor is conservative by design. It stores lines that look like durable decisions, preferences, constraints, or project facts. It skips secrets, tokens, passwords, and raw low-signal transcript text. This keeps the memory layer useful without turning it into an unsafe session recorder.

examples/claudecode-skills-memanto/requirements.txt

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+pytest>=8.2

examples/claudecode-skills-memanto/settings.example.json

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+{
+  "hooks": {
+    "UserPromptSubmit": [
+      {
+        "hooks": [
+          {
+            "type": "command",
+            "command": "python examples/claudecode-skills-memanto/skill_memory_bridge/cli.py pre"
+          }
+        ]
+      }
+    ],
+    "Stop": [
+      {
+        "hooks": [
+          {
+            "type": "command",
+            "command": "python examples/claudecode-skills-memanto/skill_memory_bridge/cli.py post"
+          }
+        ]
+      }
+    ]
+  }
+}

examples/claudecode-skills-memanto/skill_memory_bridge/__init__.py

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+"""Skill memory bridge for the Claude Code + Memanto example."""
+
+from .bridge import LocalMemoryStore, SkillEvent, SkillMemoryBridge
+
+__all__ = ["LocalMemoryStore", "SkillEvent", "SkillMemoryBridge"]