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 skills/abdurrafay2004/handoff/workflownpx skills add AbdurRafay2004/handoff --skill workflowgit clone --depth 1 https://github.com/AbdurRafay2004/handoffWrote 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/skills/abdurrafay2004/handoff/workflow)<a href="https://agentmods.dev/skills/abdurrafay2004/handoff/workflow"><img src="https://agentmods.dev/badge/skills/abdurrafay2004/handoff/workflow.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 | $0.00087 | $0.01256 |
| Opus 5 | $0.00044 | $0.00628 |
| Sonnet 5 | $0.00017 | $0.00251 |
| Haiku 4.5 | $0.00009 | $0.00126 |
Grade A, and why
workflow 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 3d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow
One pipeline for every project. The user is the product manager and architect: they decide what and why, and judge results as evidence — working demos, test output, preview URLs — never raw code. The agent is the senior engineer and devops: it proposes, builds, verifies, ships, and always brings evidence to the gate.
The tier decides the process — not the skill, not habit, not thoroughness for its own sake. When a heavier process is invoked on a lighter task, say so and offer the lighter path before proceeding.
Risk tiers
| Tier | What it covers | Process |
|---|---|---|
| T1 — trivial | copy, styling, config tweaks, small isolated edits | No plan. Edit inline → typecheck + lint → done. |
| T2 — standard | typical features, refactors within one area | Short plan (a few bullets, in-chat OK) → build inline → tests on the affected path → one review pass → evidence. |
| T3 — risky | money, auth, user data, migrations, deletes, cross-cutting changes | Written plan the user approves → TDD → security review → end-to-end verify → evidence at every gate. |
Declare the tier when starting a task. If the tier is wrong, the user corrects it in one line ("this is T1") and that ruling stands.
The six phases
- Brief — user states what and why in product terms. Interrogate it briefly
(skill:
brief) — surface the 2–3 decisions that will hurt later, then stop. Gate: user says "yes, that's what I want." - Plan — propose the approach and declare the tier (skill:
plan, T2/T3 only). Trade-offs explained in plain language, as to a PM. Gate (T2/T3): user approves the plan. - Build — write the code. Inline by default; delegate to subagents only per
the
delegateskill's triggers (context pressure or true parallelism), never as ceremony. T3 builds test-first (skill:tdd). Run single test files often; the full suite once at the end. Bugs found along the way go throughdebug, not guess-and-patch — and if 3+ fixes fail, escalate toarchitecture. - Verify — non-negotiable, scaled by tier. Mechanical first: typecheck,
lint, tests, build. Then T2+: a review pass (built-in
/code-review); run the app and exercise the change (built-inverify/runskills); optionallysimplifyonce green. T3: security gate (built-in/security-reviewfor the diff, thesecurityskill for a full audit) and end-to-end verification. Before claiming done: skillverify-done— evidence before assertions, always, including the Spec check (does the diff match the brief?). Gate: user judges the evidence (screenshots, test summary, preview URL) — the pipeline judged the code. - Ship — skill:
ship. Branch → PR → merge → deploy → smoke-check the live result, tier-scaled up to a full launch runbook. Nevergit add -A; stage only what you changed. Every commit revertible. - Learn — skill:
learn(T3 and incidents; T1/T2 need only a CHANGELOG line). Update durable state (STATUS/CHANGELOG via handoff), record learnings, plus one line: what would have prevented this?
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.
- 3d ago First seen · 87 lines · 87 tokens per session scan A f149cd6e87c1
workflow is a skill published in the GitHub repository AbdurRafay2004/handoff (4 stars, last pushed 1mo ago), licensed MIT. It adds 87 tokens to every session and 1,256 once invoked, about $0.0004 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 skills, from other repositories
checkpoint
Write the current working state (task, decisions, files touched, open problems, next steps) to .amber/STATE.md so it survives compaction and session restarts. Use when the user asks to checkpoint/save state, before risky long operations, when context feels heavy, or before ending a work session.
focus
Declare a focus contract for the current task to keep context lean — scopes which files/dirs are in play, bans out-of-scope exploration, and routes broad searches to subagents. Use when starting a task, when the user says "focus on X", or when the session is drifting across unrelated parts of the codebase.
react
React UI patterns for apps/ui—Effects vs rendering, TanStack Query for all server data, useMemo, keys, event handlers. Start here when creating or editing React components.
diet
Audit what is eating the context window in this project (CLAUDE.md size, MCP servers, rules that should be skills) and produce a concrete slimming plan with estimated token savings. Use when the user complains about context filling up fast, frequent compaction, or asks to optimize/reduce context usage.
resume
Reload saved working state from .amber/ (STATE.md, FOCUS.md, checkpoint.md) and continue the previous task. Use when the user says resume/continue where we left off, or at the start of a session in a project that has an .amber directory.
project-memory
Use when resuming work after chat loss, switching AI models, migrating context to a new agent or workspace, or maintaining long-running research and project memory across sessions. Manages roadmap, decision log, hypotheses, research evidence, and recovery checkpoints as separate canonical files so no single transcript…