Latent Briefing and KV Cache Memory Sharing Agent Skill

This skill should be used when the user asks to \"share memory between agents\", \"KV cache compaction for multi-agent\", \"orchestrator…

Context cost
4k tokensestimated from the bundle, loaded when it triggers
Bundle
2 files · 16.0 kBtext throughout, nothing executable
Licence
not declarednone named by its author
Last change
—no release on file
Servers it uses
Noneruns standalone

What it does

This skill should be used when the user asks to \"share memory between agents\", \"KV cache compaction for multi-agent\", \"orchestrator worker context\", \"latent briefing\", \"reduce worker tokens\", \"cross-agent memory without summarization\", or discusses Attention Matching compaction, recursive language models with workers, or token explosion in hierarchical agents.

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

agentdata science

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md13.0 kB · preview
--- name: latent-briefing ---
6# Latent Briefing and KV Cache Memory Sharing
7
8Hierarchical multi-agent systems often pay for the same context twice. The orchestrator accumulates a long reasoning trajectory, but each worker usually receives only a narrow text handoff such as a subtask prompt plus raw document slices. Passing the full trajectory fixes coverage but drives token cost up on every worker call. Summarization introduces latency and information loss. Retrieval helps with document access but does not preserve the orchestrator's evolving reasoning state.
9
10Latent Briefing addresses this by sharing memory at the **representation level** rather than the text level. The core idea is to compact the orchestrator trajectory in the worker model's KV cache, keeping positions that are most relevant to the **current worker task**. The method builds on **Attention Matching (AM)** KV cache compaction and adapts it for inference-time multi-agent handoff with task-guided queries, a shared token mask across heads, and robust thresholding.
11
12## When to Activate
13
14Activate this skill when:
15
16- Designing orchestrator-worker or supervisor-specialist systems where workers need access to prior orchestrator state without replaying the full trajectory as text
17- Evaluating alternatives to LLM summarization or RAG for cross-agent state transfer
18- Implementing or studying **KV cache compaction** as a first-class inference primitive, not only prefix caching of identical prompts
19- Debugging token explosion in recursive, hierarchical, or tool-heavy agent graphs
20- Interpreting benchmarks that report worker-token savings, total-token savings, compaction overhead, and accuracy together
21
22Do not activate this skill for adjacent work owned by other skills:
23- API-only stacks where internal KV tensors are inaccessible: use context-compression, memory-systems, or multi-agent-patterns.
24- Ordinary persistent memory, entity tracking, or graph retrieval: memory-systems.
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md1,798 words
Files2
Licencenot declared
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈100
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
3,900
on trigger
The instruction body and 1 supporting file, read only when the skill fires.
2.0%
of a 200k window
Ten skills this size would take about 20% of the window before you open a file.
050k100k150k200k context window

4k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Heavy. Teams tend to install this one per project rather than globally, and load it only when the job comes up.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

2 files, 16.0 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md13.0 kB
  • references/attention-matching-formulation.md3.0 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 2 files you can review in full before installing.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Latent Briefing and KV Cache Memory Sharing · 4k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/latent-briefing-and-kv-cache-memory-sharing/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/latent-briefing-and-kv-cache-memory-sharing" ] && { [ ! -e .claude/skills/latent-briefing-and-kv-cache-memory-sharing ] || { mv .claude/skills/latent-briefing-and-kv-cache-memory-sharing "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/latent-briefing-and-kv-cache-memory-sharing" .claude/skills/ && echo "Installed .claude/skills/latent-briefing-and-kv-cache-memory-sharing"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add karanmrn/latent-briefing-and-kv-cache-memory-sharing

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/latent-briefing-and-kv-cache-memory-sharing/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/latent-briefing-and-kv-cache-memory-sharing/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/latent-briefing-and-kv-cache-memory-sharing" ] && { [ ! -e ~/.claude/skills/latent-briefing-and-kv-cache-memory-sharing ] || { mv ~/.claude/skills/latent-briefing-and-kv-cache-memory-sharing "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/latent-briefing-and-kv-cache-memory-sharing" ~/.claude/skills/ && echo "Installed ~/.claude/skills/latent-briefing-and-kv-cache-memory-sharing" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/latent-briefing-and-kv-cache-memory-sharing/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where. It appears as latent-briefing in Gemini CLI, Codex, Copilot and Grok (its own name); Claude Code lists it by the folder name, latent-briefing-and-kv-cache-memory-sharing.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Versionnot versioned
Publishedno release date on file
PriceFree
Referencekaranmrn/latent-briefing-and-kv-cache-memory-sharing

Versions

Its author publishes no version number, so there is nothing here to pin to: what you install is the folder as it stands today. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

Pinning

Nothing to pin to: this skill carries no version number of its own. What you install is what the folder holds on the day you install it.

Reviews

—no reviews yet

Nobody has reviewed this skill yet. The rating is the mean of the reviews written here, so there is none until somebody writes the first.

Sign in to review it

A review is tied to an account so it can be answered, edited and taken down by the person who wrote it.

Sign in
Who can post

Anybody with an account, one review each. It carries the version that was current when you wrote it, and the publisher may reply once.

Publisher
Servers0
Claim this skill