Session Handoff
sickn33/agentic-awesome-skills
A skill your agent uses when context approaches capacity, before /clear or /compact, when switching tasks, or when ending a coding session: produces a structured handoff artifact for the next session.
You CAN read other sessions' conversations. An agent skill from vlinx-io/VelaTerm.
$ npx skills add vlinx-io/VelaTerm --skill vrefer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install vlinx-io/VelaTerm vrefer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/vrefer .claude/skills/vrefer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "vrefer" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/skills/vrefer into .claude/skills/vrefer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vrefer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/vlinx-io/VelaTerm/tree/dev/skills/vreferType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add vlinx-io/VelaTerm --skill vrefer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install vlinx-io/VelaTerm vrefer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/vrefer .agents/skills/vrefer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "vrefer" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/skills/vrefer into .agents/skills/vrefer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vrefer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vlinx-io/VelaTerm --skill vrefer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install vlinx-io/VelaTerm vrefer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/vrefer .cursor/skills/vrefer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "vrefer" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/skills/vrefer into .cursor/skills/vrefer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vrefer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/vlinx-io/VelaTerm.git --path skills/vrefer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add vlinx-io/VelaTerm --skill vrefer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install vlinx-io/VelaTerm vrefer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/vrefer .gemini/skills/vrefer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "vrefer" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/skills/vrefer into .gemini/skills/vrefer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vrefer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install vlinx-io/VelaTerm vreferInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add vlinx-io/VelaTerm --skill vrefer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/vrefer .github/skills/vrefer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "vrefer" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/skills/vrefer into .github/skills/vrefer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vrefer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vlinx-io/VelaTerm --skill vrefer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install vlinx-io/VelaTerm vrefer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vlinx-io/VelaTerm.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/vrefer .opencode/skills/vrefer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "vrefer" agent skill from https://github.com/vlinx-io/VelaTerm/tree/dev/skills/vrefer into .opencode/skills/vrefer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vrefer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
vreferYou CAN read other sessions' conversations. An agent skill from vlinx-io/VelaTerm.
Vrefer is an agent skill from vlinx-io/VelaTerm. You CAN read other sessions' conversations. Sessions are not isolated from you here: this reads any other vlx-term session's transcript, whether or not it is running. Use it whenever the user points at another conversation — naming a session, or saying things like "that other session", "last time", "the other branch", "how did we solve this before", "what did it decide" — in any language. Never tell the user you cannot see other sessions, and never ask them to copy content over by hand; read it yourself with…
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: VelaTerm = Codex + iTerm2, The Best ADE for AI Coding. The licence is MIT.
Read from SKILL.md and the folder at commit 98b5f2f. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
Bash(vrefer:*)From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Vrefer loads about 1.7k tokens when it runs. Until then it costs about 164 tokens; SKILL.md has 935 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from vlinx-io/VelaTerm at commit 98b5f2f, republished under its MIT licence (© vlinx-io). 935 words, ~1,693 tokens.
.claude/skills/vrefer/SKILL.md (or your agent's skills folder).vrefer prints the conversation of another vlx-term session. The target session does not have to be
running, and nothing is sent to it — this only reads what it already recorded.
Reach for this the moment a request depends on what another conversation contains:
vsearch returned a hit and you need the conversation around the snippet.These come in whatever language the user speaks; the trigger is the meaning, not the wording.
The failure to avoid: answering "I have no access to other sessions" or asking the user to paste the
content over. That is wrong here — you do have access, and this is how. If you are unsure which session
they mean, run vrefer --list or vsearch and ask, rather than declining.
Search first, then refer. When the target is not named outright, run vsearch and let it hand you
the id instead of paging through vrefer --list.
vrefer <session> [--last N] [--range A:B] [--json]
vrefer <session> --ask "<question>" [--with KIND] [--timeout SECONDS]
vrefer --list<session> accepts, in this order: a full session id, an id prefix of at least 8 characters, an exact
session name, or a unique substring of a name. Quote names containing spaces. Prefer the id that
vsearch printed — names can be ambiguous.
vrefer <session> returns the entire transcript. Referencing another session means wanting what it says,
and a partial record read as a whole one leads to confident wrong conclusions.
Narrow it only when you actually want less:
--last N gives just the last N messages, for when you only need to know where that session got to.--range A:B gives an exact slice by message index, zero-based, A included and B excluded. The msg N
anchors in vsearch output are these indices, so --range 40:60 reads around a hit at message 50.--ask puts the reading somewhere else. A short-lived answering agent gets the session context and your
question, and only its answer comes back — the transcript never enters your context.
vrefer 2feead2c --ask "how did the throttling design end up, and why"Use it when the target is long and you know what you are after. Read the transcript directly when it is short, or when you need its actual wording rather than someone's reading of it. A one-line lookup does not justify starting an agent: that run costs the user real tokens and takes tens of seconds.
The default context mode is Full transcript, preserving the original behavior: the answering agent reads the complete transcript directly. The user can instead enable Summarize first in Settings → Behavior → Session reference context and choose one global summary Agent, model, and reasoning effort. In that mode VelaTerm first compresses the transcript with exactly that selection, searches the same session for terms relevant to the question, then gives the answering agent both the summary and original search excerpts. Do not guess which mode is enabled; the attribution line reports it.
Summaries are generated for each question and are not cached. Summarizing reduces the final answering agent's context, but processing the full transcript first may increase total time and token usage.
The reply opens with a line naming which agent answered, how many messages were covered, and whether the context was full or summarized. Quote it as that agent's reading of another session, not as that session's own words.
--with <kind> forces the answering agent (claude, codex, opencode, pi, omp, cursor, copilot, or
grok) instead of letting one be chosen. It does not override the global pre-summary selection.
--timeout <seconds> gives the AI stages a shared time budget, 120 seconds by default. HTTP waiting
allows another 15 seconds for the response, with a minimum of 30 seconds. Transcript reads and synchronous
index refreshes cannot yet be canceled midway.
--last and --range limit ordinary reads and fallback output; --ask still considers the full session.
If asking cannot happen — nothing installed, the run failed, the feature is switched off — the transcript
comes back instead, with the reason on stderr and exit code 0. You still have what you asked for; check
stderr before treating the output as an answer. With --json, also check askFailed; the warning remains
on stderr while stdout contains valid JSON.
The header names the session, its kind, its total message count, and the window shown. Each message is labelled with its index, role, time, and the tools that turn used. When earlier messages exist, the last line gives you the exact command to read them.
vself [session] --json; for associated plan-execute workflows and execute sessions, use vflow list [session]. vrefer --list identifies sessions but does not itself return their hierarchy.VLX_* environment
variables and vrefer on PATH. If it reports "not inside a VelaTerm session", the command is simply
unavailable here.© vlinx-io, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/vrefer of vlinx-io/VelaTerm.
Open the folder on GitHubat commit 98b5f2f
Vrefer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Vrefer this skillvlinx-io/VelaTerm | 275 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Session Handoffsickn33/agentic-awesome-skills | 47k | — | ~1.8k | Automated safety check: Notes | MIT | |
| Session Persistruvnet/ruflo | 74k | — | ~415 | Automated safety check: Notes | MIT | |
| Sessionanthropics/claude-for-legal | 9.6k | 3 repos | ~478 | Automated safety check: Pass | Apache-2.0 | |
| Session History Searchslopus/happy | 24k | — | ~3.1k | Automated safety check: Pass | MIT | |
| Cost Conversationruvnet/ruflo | 74k | — | ~407 | Automated safety check: Notes | MIT |
sickn33/agentic-awesome-skills
A skill your agent uses when context approaches capacity, before /clear or /compact, when switching tasks, or when ending a coding session: produces a structured handoff artifact for the next session.
ruvnet/ruflo
Persist and restore agent sessions across conversations with state snapshots
anthropics/claude-for-legal
Run a focused N-question study session on a subject — MBE, essay, or flashcards.
slopus/happy
Searches past Claude Code, Codex and Cursor sessions and summarizes what was worked on, tried or decided, using extraction scripts instead of reading raw logs.
ruvnet/ruflo
Per-conversation cost view — list every session in cost-tracking with started-at, message count, top model, and total cost
garrytan/gbrain
Import AI-assistant chat exports (ChatGPT, Claude, Perplexity) and agent session transcripts into the brain as one dated page per conversation under conversations/, validate each page against the…
vlinx-io/VelaTerm
Assess an immutable patch artifact's program impact, regression risk, and auto-merge eligibility.
vlinx-io/VelaTerm
Explicitly spawn a standalone child session under the current vlx-term session, passing the task in as its first message (mirrors spawntask).
vlinx-io/VelaTerm
A skill your agent uses when the user asks for a deep, exhaustive, multi-pass, or variance-reducing repository-wide or scoped-path Codex Security scan.
vlinx-io/VelaTerm
Define, review, or update SECURITY.md guidance for a repository or component.
vlinx-io/VelaTerm
Track validated Codex Security findings in Linear, Jira, GitHub issues, or draft GitHub security advisories.
vlinx-io/VelaTerm
Use only when the user explicitly requests verification that a security fix remediates a reported vulnerability.
You CAN read other sessions' conversations. An agent skill from vlinx-io/VelaTerm. Vrefer is an agent skill from vlinx-io/VelaTerm. You CAN read other sessions' conversations.
Vrefer fits situations like: the user points at another conversation — naming a session; saying things like that other session; the other branch; how did we solve this before.
Run `npx skills add vlinx-io/VelaTerm --skill vrefer -a claude-code`. Or copy the skill folder (skills/vrefer in vlinx-io/VelaTerm) into .claude/skills/vrefer in your project. Claude Code loads it when a task matches its description.
Run `npx skills add vlinx-io/VelaTerm --skill vrefer -a codex`. Or copy the skill folder (skills/vrefer in vlinx-io/VelaTerm) into .agents/skills/vrefer in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vlinx-io/VelaTerm --skill vrefer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vrefer, .gemini/skills/vrefer, .github/skills/vrefer and .opencode/skills/vrefer in your project.
SKILL.md names no scripts, command-line tools or credentials: Vrefer is instructions for the agent only. Its frontmatter pre-approves these tools: Bash(vrefer:*).
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Vrefer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Vrefer: Session Handoff (sickn33/agentic-awesome-skills, 47k stars), Session Persist (ruvnet/ruflo, 74k stars), Session (anthropics/claude-for-legal, 9.6k stars) and Session History Search (slopus/happy, 24k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
vlinx-io (a GitHub user) maintains it in vlinx-io/VelaTerm, which has 275 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on October 7, 2026.
Source: vlinx-io/VelaTerm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.