evidence-handoff skill: it reads the relevant project material and drafts a handoff that separates observations, test results and open questions. The first exercise stays local. An optional section explains how to share the result through AMS when independent tasks need a common conversation.
Claude Code documentation reviewed 5 November 2026. The example targets local terminal sessions; cloud and account-synced skills have different discovery rules.
Skills, agents, instructions and MCP
Anthropic’s subagent documentation explains separate worker contexts; its memory documentation covers project instructions. MCP supplies a tool connection, while a skill can describe how to use available tools.
A skill normally runs in the current conversation. Adding
context: fork requests a subagent context; a skill is not inherently another agent. Native teams and messaging are separate features: see running multiple Claude Code agents.
Prerequisites
- A working local Claude Code installation and access to a project you can read. Follow Anthropic’s quickstart if needed.
- Permission to add a skill folder in that project, or use your personal skills directory instead.
- A specific handoff question and a file the reviewer can inspect, such as the project’s
README.md.
Choose the installation scope
Use the project location for this walkthrough. Local personal files do not automatically transfer to cloud sessions. Nested directories, linked worktrees and account-synced skills have additional rules; consult Anthropic’s skill location reference for your environment.
Create a small collaboration skill
1. Create the folder
From the intended project root:~/.claude/skills/evidence-handoff throughout instead.
2. Write SKILL.md
Create.claude/skills/evidence-handoff/SKILL.md with this content:
--- on the first line. name and description identify the workflow; $ARGUMENTS receives the text after the command. disable-model-invocation: true makes this example manual. See the current frontmatter reference.
The example deliberately leaves sending out of the procedure. A reviewer can inspect the evidence before deciding whether a teammate needs it. It also avoids pre-approving tools. A skill’s allowed-tools field grants permissions for listed tools; it is not a tool allowlist that blocks everything else. Use Claude Code’s permission settings for access controls.
3. Load and invoke it
For a static format check on Claude Code v2.1.233 or later, run this in the shell:evidence-handoff. If you added the folder during an existing session, run /reload-skills and check again. These are Claude Code prompt commands, not shell commands; Anthropic documents both in its command reference.
Then send a message beginning with:
README.md.
4. Verify the result
For this exercise, a successful response should:- Identify the file inspected and cite the lines supporting its setup findings.
- Identify the Git revision and relevant uncommitted changes, or explain why those are unavailable.
- State that tests were not run, without turning a README instruction into a claim that a test passed.
- Give the reviewer a next action, such as checking one unresolved setup requirement.
- Leave the project files unchanged and keep the handoff in the conversation.
git status --short before and after invocation; creating the skill itself is an expected change. A command appearing in the menu proves discovery, while an accurate report demonstrates the procedure’s usefulness.
Try a second invocation against a path you know does not exist. The expected result is an explicit missing-source limitation, with no invented findings or successful checks. This tests the part of the handoff most likely to mislead another agent.
For repeat use, try realistic handoff questions in fresh sessions and compare the reports against a short checklist. Anthropic’s authoring guidance recommends concrete examples and evaluation rather than relying on one successful response.
Control activation and share the skill
For automatic selection, removedisable-model-invocation: true and keep a precise description of when to use the skill. user-invocable: false instead hides a skill from direct user invocation. Existing .claude/commands/ files still work, but use a SKILL.md folder for new skills. See invocation controls.
To install a reviewed skill from someone else, put its complete folder in your chosen skill location, preserving any relative supporting files, then repeat the discovery and behavior checks above. Read its instructions, scripts and permission grants before using it. A Markdown procedure can still direct consequential actions.
For team distribution, review the project skill alongside your code, or use Anthropic’s plugin installation workflow for a trusted plugin. This walkthrough does not install a marketplace package or publish a plugin.
Optional: share a verified handoff through AMS
Use AMS when separate tasks or tools need a shared channel for findings, ownership decisions and review requests. Keep the local skill above as the drafting step. Claude Code’s native subagents, teams and skill loading work without AMS. For the CLI path, first complete the AMS quickstart and deliberately enable the intended folder using repository workspace setup. Have each agent run the following from its actual working folder:enabled: true, continue:
(more available). If activation is disabled or invalid, leave AMS off and resolve setup deliberately.
After reviewing the draft and authorizing a send to that channel, save the approved text to a local file and use:
SKILL.md neither configures MCP nor authenticates AMS. The example is a user-authored teaching skill, not an AMS skill package. For a full tester/builder exchange, see Claude Code and Codex together.
Troubleshooting
For discovery and trigger failures, use Anthropic’s skill troubleshooting guide. Keep project-wide rules in your shared instructions so the workflow remains useful beyond a single invocation.
The example was checked against the linked documentation, and the extracted
SKILL.md passed a local claude plugin validate check. No authenticated Claude Code skill run or live AMS exchange was performed for this tutorial. Run the exercise in your own environment to verify discovery, permissions and output quality.