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/willseltzer/claude-handoff/creategit clone --depth 1 https://github.com/willseltzer/claude-handoffWhat 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 | $0.00014 | $0.01015 |
| Opus 5 | $0.00007 | $0.00508 |
| Sonnet 5 | $0.00003 | $0.00203 |
| Haiku 4.5 | $0.00001 | $0.00102 |
Grade A, and why
create 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 2d 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 — 142 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create a HANDOFF.md file that enables ANY AI coding agent to continue this work seamlessly.
Gather Context First
Run these commands to understand current state:
git status- see uncommitted changesgit diff --stat- see what files changedgit log --oneline -5- recent commits from this session
Review the conversation history to extract:
- The original task/goal
- What was completed
- What was tried and didn't work (critical - saves hours)
- Key decisions and their rationale
- User preferences expressed during the session
- Error messages encountered and how they were resolved
Write HANDOFF.md
Use this structure (omit empty sections, but NEVER omit Failed Approaches if any exist):
# Handoff: [Brief Task Title]
**Generated**: [date/time]
**Branch**: [git branch]
**Status**: [In Progress / Blocked / Ready for Review]
## Goal
[1-2 sentences: what the user wants to achieve]
## Completed
- [x] [Specific completed item]
- [x] [Another completed item]
## Not Yet Done
- [ ] [Remaining task - be specific]
- [ ] [Another remaining task]
## Failed Approaches (Don't Repeat These)
[IMPORTANT: Always include this if anything was tried and abandoned. Be specific:]
- What was attempted
- Why it failed (error message, performance issue, design flaw)
- Why the current approach is better
Example:
> Tried using passport.js for OAuth but it conflicted with existing Express middleware (req.user was undefined). Switched to oauth4webapi which works directly with fetch.
## Key Decisions
| Decision | Rationale |
|----------|-----------|
| [Choice made] | [Why this approach] |
## Current State
**Working**: [What's functional right now]
**Broken**: [What's not working, error messages if relevant]
**Uncommitted Changes**: [Summary of unstaged/staged changes]
## Files to Know
| File | Why It Matters |
|------|----------------|
| `path/to/key/file.ts` | [Brief description] |
## Code Context
[Include actual code the next agent needs. Don't describe - show:]
**Key interfaces/signatures** (so the agent knows how to call/modify them):
```typescript
// Example: hook signature
function useAuth(): { user: User | null; login: (creds: Credentials) => Promise<void> }
API request/response shapes (if backend work):
// POST /api/resource - example response
{ "id": 123, "status": "created" }
Non-obvious logic (anything tricky that isn't self-documenting)
Resume Instructions
[Be extremely specific. Not "test the feature" but step-by-step with expected outcomes:]
- [Setup step if needed - migrations, env vars, etc.]
- [First action with exact command or file to edit]
- [Verification step with expected outcome]
- Expected: [what should happen]
- If it fails: [what to check]
Example:
- Run
alembic upgrade headto apply migrations - Start server:
./start.sh - Test login flow: POST to /api/login with [email protected] / testpass
- Expected: 200 response with { token: "..." }
- If 401: Check user exists in DB
Setup Required
[Only if there are prerequisites the next agent needs:]
- Environment variables:
API_KEY,DATABASE_URL - Test accounts: [email protected] / password123
- Required services: Redis must be running on :6379
Edge Cases & Error Handling
[Document known edge cases and how they're handled - or should be:]
- What happens if [X fails]? → [current behavior or "not handled yet"]
- What if user does [Y]? → [expected behavior]
Warnings
[Gotchas, things that look wrong but are intentional, or traps to avoid]
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.
- 2d ago First seen · 142 lines · 14 tokens per session scan A 6ffd3a02d373
create is a command published in the GitHub repository willseltzer/claude-handoff (141 stars, last pushed 8mo ago), licensed MIT. It adds 14 tokens to every session and 1,015 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.