How do I install the Session Summary skill?

Run npx skillmds@latest add oimiragieo/session-summary-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Session Summary safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Session Summary?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Session Summary free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Session Summary?

oimiragieo (@oimiragieo) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Session Summary by oimiragieo — Agent Skill

Name: Session Summary
Author: oimiragieo

Session Summary

Compress a session's conversation history into a portable summary that can be re-injected after /clear. Use this skill when context is filling up and the agent needs to recover state after clearing. Works even when Claude Code's own auto-compact has failed because gotcontext runs the summarization on its own infra. Trigger phrases include "summarize this session", "I need to clear context but keep what we built", "compact failed help me recover", "save this conversation before reset".

oimiragieo Updated Sep 22, 2026 0 repo stars

File contents

session-summary

When this skill is the preferred path

Context fill is high (90%+ of the window) and /compact is failing or about to fail. The agent needs to clear and resume without losing the work it has done so far. gc_session_summary produces a portable summary the agent can re-inject after /clear.

This skill is the natural pair to gc_pre_flight. When pre_flight returns the clear_first verdict, the workflow is:

Call gc_session_summary with the conversation history.
Use /clear (Claude Code's built-in).
Send the returned restoration_instructions as your first user message in the cleared session.
Call gc_pre_flight again with the next prompt — context fill is now low, you'll get send_compressed or send_as_is.

How to use it

Call gc_session_summary with one of:

messages — structured conversation history as a list of {role, content} dicts. Roles: user, assistant, system, tool. Preferred when available.
text — concatenated conversation as a plain string. Use when structured messages aren't available.

If both are passed, messages wins.

Optional:

keep_facts — facts the summary MUST preserve verbatim (file paths, decisions, blockers, identifiers). Each item is prepended to the summary as a bullet point and not compressed.
target_tokens — max size for the summary. Default 4000.

What you get back

{
  "summary": "<compressed-summary-string>",
  "key_facts": ["...", "..."],
  "tokens_in_original": 184000,
  "tokens_in_summary": 4200,
  "compression_ratio": 0.023,
  "restoration_instructions": "After /clear, send this as your first user message...",
  "recommendation": "Summary 97.7% smaller than original. Run /clear, then send..."
}

The restoration_instructions field is canonical — copy it into your next user message verbatim and the agent resumes with the compressed context attached.

Why this skill exists

Auto-compaction can be token-expensive: it tends to resubmit a large bloated context for summarization once the window is nearly full, so a single compaction event can cost tens to hundreds of thousands of tokens. Our summarization runs OUTSIDE the exhausted Claude context — it works when Claude Code's own auto-compact would fail.
A well-known limitation: when nearly all of the 200k-token context window is used, there isn't enough headroom left to compact. This skill runs summarization on separate infra, so it's the recovery path for exactly that situation.
LocalLLaMA pattern: "Treat the context window like RAM and the scratchpad like disk." This skill IS the scratchpad.

Failure-mode contract

Never raises to the agent. If the compression service is degraded, the response returns the truncated head of the conversation as a fallback summary plus a recommendation field flagging the degradation. The agent always gets a structured response it can re-inject.

Plan availability

Available on every plan including Free. Volume is governed by your existing per-month compression quota — same posture as gc_pre_flight.

---name: session-summary-2description: Compress a session's conversation history into a portable summary that can be re-injected after /clear. Use this skill when context is filling up and the agent needs to recover state after clearing. Works even when Claude Code's own auto-compact has failed because gotcontext runs the summarization on its own infra. Trigger phrases include "summarize this session", "I need to clear context but keep what we built", "compact failed help me recover", "save this conversation before reset".---# session-summary## When this skill is the preferred pathContext fill is high (90%+ of the window) and `/compact` is failing orabout to fail. The agent needs to clear and resume without losing thework it has done so far. `gc_session_summary` produces a portablesummary the agent can re-inject after `/clear`.This skill is the natural pair to `gc_pre_flight`. When pre_flightreturns the `clear_first` verdict, the workflow is:1. Call `gc_session_summary` with the conversation history.2. Use `/clear` (Claude Code's built-in).3. Send the returned `restoration_instructions` as your first user message in the cleared session.4. Call `gc_pre_flight` again with the next prompt — context fill is now low, you'll get `send_compressed` or `send_as_is`.## How to use itCall `gc_session_summary` with one of:- `messages` — structured conversation history as a list of `{role, content}` dicts. Roles: `user`, `assistant`, `system`, `tool`. Preferred when available.- `text` — concatenated conversation as a plain string. Use when structured messages aren't available.If both are passed, `messages` wins.Optional:- `keep_facts` — facts the summary MUST preserve verbatim (file paths, decisions, blockers, identifiers). Each item is prepended to the summary as a bullet point and not compressed.- `target_tokens` — max size for the summary. Default 4000.## What you get back```json{ "summary": "<compressed-summary-string>", "key_facts": ["...", "..."], "tokens_in_original": 184000, "tokens_in_summary": 4200, "compression_ratio": 0.023, "restoration_instructions": "After /clear, send this as your first user message...", "recommendation": "Summary 97.7% smaller than original. Run /clear, then send..."}```The `restoration_instructions` field is canonical — copy it into yournext user message verbatim and the agent resumes with the compressedcontext attached.## Why this skill exists- Auto-compaction can be token-expensive: it tends to resubmit a large bloated context for summarization once the window is nearly full, so a single compaction event can cost tens to hundreds of thousands of tokens. Our summarization runs OUTSIDE the exhausted Claude context — it works when Claude Code's own auto-compact would fail.- A well-known limitation: when nearly all of the 200k-token context window is used, there isn't enough headroom left to compact. This skill runs summarization on separate infra, so it's the recovery path for exactly that situation.- LocalLLaMA pattern: "Treat the context window like RAM and the scratchpad like disk." This skill IS the scratchpad.## Failure-mode contractNever raises to the agent. If the compression service is degraded,the response returns the truncated head of the conversation as afallback summary plus a `recommendation` field flagging thedegradation. The agent always gets a structured response it canre-inject.## Plan availabilityAvailable on every plan including Free. Volume is governed by yourexisting per-month compression quota — same posture as`gc_pre_flight`.

Frequently asked questions