Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/khanh-vu/claude-force/handoffgit clone --depth 1 https://github.com/khanh-vu/claude-forceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/khanh-vu/claude-force/handoff)<a href="https://agentmods.dev/commands/khanh-vu/claude-force/handoff"><img src="https://agentmods.dev/badge/commands/khanh-vu/claude-force/handoff.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00006 | $0.03367 |
| Opus 5 | $0.00003 | $0.01684 |
| Sonnet 5 | $0.00001 | $0.00673 |
| Haiku 4.5 | $0.00001 | $0.00337 |
Grade A, and why
handoff scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 588 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Handoff Command
Create structured handoff documentation for seamless session continuation.
When to Use
Perfect for:
- End of work session (before closing)
- Before context window fills up
- Natural breakpoints (workflow completion)
- Switching to different task
- Team handoffs (sharing context)
Timing:
- Sessions > 2 hours: Recommended
- Before major breaks: Essential
- Complex workflows: Every phase completion
Basic Usage
Generate handoff for current session:
/handoff
What happens:
- Analyzes current session state
- Extracts workflow progress
- Captures decision context (WHY you made choices)
- Prioritizes remaining work (P1/P2/P3)
- Includes governance and performance metrics
- Auto-detects confidence level
- Saves to
.claude/whats-next.mdand archives
Output:
## Session Handoff
**Session**: session-20251116-143022
**Started**: 2025-11-16 14:30
**Duration**: 4h 15m
**Status**: 🟢 High Confidence
---
## Original Task
**Title**: Build Product Catalog UI
**Priority**: 🔴 High
**Workflow**: full-stack-feature
Create responsive product catalog with filters, search, and pagination.
Support 1000+ products with good performance.
---
## Session Summary
**Key Decisions Made:**
- Chose PostgreSQL array types for product tags (better query performance than JSON)
- React Query for API caching with 5min stale time (balance freshness/performance)
- Filter state in URL params for shareable links
- Pagination set to 50 items/page (UX testing showed optimal)
**Critical Insights:**
- Backend API already handles sorting, don't duplicate in frontend
- Product images need lazy loading (performance issue discovered)
- Search debouncing at 300ms feels responsive (tested)
**Conversation Highlights:**
Spent first hour on architecture decisions (API design, state management).
Implemented core components mid-session. Discovered performance issue with
images late in session, added to todos for next session.
---
## Progress Summary
**Overall**: 5 of 8 agents complete (62%)
✅ frontend-architect
✅ database-architect
✅ backend-architect
✅ python-expert
✅ ui-components-expert
🔄 frontend-developer (Next - 60% complete)
⏳ qc-automation-expert
⏳ deployment-integration-expert
---
## Work Completed
**Completed Items:**
- ✅ Designed component architecture
- ✅ Created database schema with indexes
- ✅ Built REST API endpoints (/products, /search, /filter)
- ✅ Implemented ProductCard, FilterBar, SearchBox components
**Files Modified:**
- `src/components/ProductCard.tsx`: Created product card with image, price, tags
- `src/components/FilterBar.tsx`: Filter UI with category, price range, tags
- `src/api/products.py`: REST endpoints with pagination, sorting, filtering
- `database/schema.sql`: Product table with GIN index on tags array
**Agent Outputs:**
- **frontend-architect**: Component tree, state flow diagram, routing structure
- **database-architect**: Schema with indexes, migration scripts
- **backend-architect**: API spec (OpenAPI), caching strategy
- **python-expert**: Optimized queries with SQLAlchemy, bulk loading
- **ui-components-expert**: Responsive components with Tailwind CSS
---
## Next Steps
**PRIORITY 1 (Critical Path):**
- 🔴 Complete ProductList container component (ties everything together)
- 🔴 Implement lazy loading for product images (performance blocker)
**PRIORITY 2 (High Value):**
- 🟡 Add loading states and error boundaries
- 🟡 Implement pagination controls
**PRIORITY 3 (Nice to Have):**
- 🟢 Add sorting options (name, price, date)
- 🟢 Add filter presets (e.g., "On Sale", "New Arrivals")
**Dependencies:**
- QA testing depends on ProductList completion
- Deployment depends on QA passing
---
## Active Context
**Most Relevant Right Now:**
- 💡 ProductList needs virtualization for 1000+ products (react-window library)
- 💡 Images hosted on CDN, use srcset for responsive loading
- 💡 Filter state structure: `{ category: string[], priceRange: [min, max], tags: string[] }`
**Known Blockers:**
- ⚠️ CDN access not yet configured for images
- Mitigation: Use placeholder images for development, add todo for ops
**Open Questions:**
- ❓ Should we pre-load next page of results? (UX vs bandwidth trade-off)
- ❓ Real-time stock updates or polling? (need product owner input)
---
## Quality Status
**Last Validation**: ✅ All Checks Pass
- Scorecard: 12/12 ✅
- Write Zone: Updated ✅
- Secrets: None detected ✅
- Format: Valid ✅
---
## Cost & Performance
💰 **Total Cost**: $2.45
⏱️ **Execution Time**: 4h 15m
🤖 **Agents Run**: 5 of 8
📊 **Tokens Used**: 45,230 tokens
📈 **Context Window**: 35.2% used
---
## Technical Context
Key decisions and gotchas:
- Using PostgreSQL array types for tags (better than JSONB for this use case)
- React Query configured with `staleTime: 300000` (5 minutes)
- Filter state managed in URL params: `?category=electronics&priceMin=100&priceMax=500`
- API pagination: limit/offset (consider cursor-based if performance issues)
- Image CDN URLs follow pattern: `${CDN_BASE}/products/${productId}/${size}.webp`
- Frontend validation matches backend (shared validation lib recommended)
---
## To Resume
**To Resume This Session:**
1. **Review this handoff** - Read session summary and active context above
2. **Start with**: Complete ProductList container component (PRIORITY 1)
3. **Continue workflow**: `/run-agent frontend-developer` (will resume from 60%)
4. **After frontend**: Run `/run-agent qc-automation-expert` for testing
5. **Validate**: Run `/validate-output` before proceeding to deployment
**Quick Start Command**:
/run-agent frontend-developer
---
**Generated**: 2025-11-16 18:45:22
**Saved to**: `.claude/handoffs/handoff-2025-11-16-184522.md`
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 588 lines · 6 tokens per session scan A d1d94052fd76
handoff is a command published in the GitHub repository khanh-vu/claude-force (5 stars, last pushed 9mo ago), licensed MIT. It adds 6 tokens to every session and 3,367 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.