session-handoff

session-handoff is a skill for Claude Code from ai-analyst-lab/ai-analyst. It costs 242 tokens per session (1,602 once invoked), scanned A, original, MIT.

A procedure for recording important work details before a conversation or long workflow ends. It saves progress, task details, local files, external document links, and authentication state so later work can continue.

In plain words
What is it for?
Use it during long, multi-step analyses and workflows involving external files, especially before pausing or handing work to another session.
Why use it?
It prevents context limits or a new session from losing the information needed to pick up a task. It also preserves IDs for resources created in services such as Google Drive or Docs.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Good fit Use it during long, multi-step analyses and workflows involving external files, especially before pausing or handing work to another session.

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Install with agentmods
npx agentmods add skills/ai-analyst-lab/ai-analyst/session-handoff
Install

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.

Any agent
npx skills add ai-analyst-lab/ai-analyst --skill session-handoff
Clone the repo
git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst

Made for: Claude Code.

Wrote 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.

agentmods badge for session-handoff

README.md
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Your own site
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agentmods 80×15 button for session-handoff

Your own site · 80×15
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Per session 242 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,602 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00242 $0.01602
Opus 5 $0.00121 $0.00801
Sonnet 5 $0.00048 $0.00320
Haiku 4.5 $0.00024 $0.00160

Measured 2d ago against content hash b9bbcf862796, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-13, from the pricing page.

Security

Grade A, and why

session-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 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.

.claude/skills/session-handoff/SKILL.md · 177 lines

How it starts

The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: Session Handoff

Purpose

Preserve critical state when a session approaches context limits, so the next session (or /resume-pipeline) can pick up seamlessly. Prevents lost work when context compaction occurs or the user starts a new conversation.

When to Apply

Automatically when:

  • A long multi-step workflow is in progress
  • A multi-step Google Workspace workflow is in progress
  • The pipeline involves external resource IDs (doc IDs, slide IDs, Drive folders)
  • Before any pause point where the user might come back later

What to Save

Write to the EXACT path working/session_state.yaml (not session_state_handoff.yaml or any variant). The /resume-pipeline command looks for this specific file path.

This file MUST be comprehensive, regardless of how simple the handoff seems. Capture ALL of the following information:

Required Fields (always include):

  • ✅ Dataset name and connection details
  • ✅ Task description (what analysis/work is in progress)
  • ✅ Pipeline progress (what's complete, what's next)
  • ✅ All external resource IDs (Google Docs, Slides, Drive files) with URLs
  • ✅ Local file inventory (working/ and outputs/ directories)
  • ✅ Auth state (user email, last verified date)
  • ✅ Known issues or blockers (write "None" if no issues)
  • ✅ Resume instructions (step-by-step guide)

The Template (Use This Every Time)

Use the complete template. Fill every section (an empty section is "None"), because the next session has no other context.

Template:

# Session State — auto-generated by session-handoff skill
# Last updated: {{DATE}} {{TIME}}

dataset: "{{DATASET_NAME}}"
task: "brief description of what we're doing"

# External resource IDs (Google Workspace, etc.)
resources:
  google_doc:
    id: "18MTagnf_z5..."
    title: "Document Title"
    url: "https://docs.google.com/document/d/18MTagnf.../edit"
    status: "content complete, needs formatting review"
  google_slides:
    id: "1in6mkRf..."
    title: "Deck Title"
    url: "https://docs.google.com/presentation/d/1in6mkRf.../edit"
    status: "12 slides built, reviewer passed"
  drive_folder:
    id: "1PV9ols..."
    name: "Folder Name"
  drive_files:
    - id: "1abc..."
      name: "01_chart.png"
    - id: "2def..."
      name: "02_chart.png"

# Pipeline progress
pipeline:
  last_completed_step: "chart generation"
  current_step_status: "narrative draft 80% complete — context and findings done, recommendations need 2 more paragraphs"  # Use this for partially-complete steps
  next_step: "Google Doc creation"
  steps_remaining:
    - "Create Google Doc with proper image placement"
    - "Run Google Doc Reviewer"
    - "Final review of both deliverables"

# Local file inventory
local_files:
  charts:
    - outputs/charts/01_height_crossover.png
    - outputs/charts/02_height_gap.png
  data:
    - outputs/ms_case_study/data.csv
  working:
    - working/narrative_draft.md
    - working/storyboard.md

# Auth state (REQUIRED)
auth:
  google_email: "[email protected]"  # If not provided by user, check working files or note "unknown — verify at resume"
  last_verified: "2026-03-05"
  notes: "Tokens expire between sessions — expect re-auth"

# Known issues or blockers (REQUIRED — use "None" if no issues)
issues:
  - "Google Doc images overlap with text — needs rebuild with proper placement"
  - "Doc heading formatting was applied manually, may need re-check"
  # OR if no issues:
  # - "None — all work completed successfully"

# Resume instructions (REQUIRED)
resume:
  command: "/resume-pipeline"
  steps:
    - "Verify auth for {{auth.google_email}}"
    - "Load external resources"
    - "Continue from: {{pipeline.next_step}}"

Read the full file on GitHub · 177 lines

Changes

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.

  1. 2d ago First seen · 177 lines · 242 tokens per session scan A b9bbcf862796

Subscribe to this mod's changes

session-handoff is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (298 stars, last pushed 3d ago), licensed MIT. It adds 242 tokens to every session and 1,602 once invoked, about $0.0012 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 2026-09-12.

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