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.
npx skills add navendubrajesh/context-management-for-agents --skill copilot-session-managementgit clone --depth 1 https://github.com/navendubrajesh/context-management-for-agentsWrote 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.
[](https://agentmods.dev/skills/navendubrajesh/context-management-for-agents/copilot-session-management)<a href="https://agentmods.dev/skills/navendubrajesh/context-management-for-agents/copilot-session-management"><img src="https://agentmods.dev/badge/skills/navendubrajesh/context-management-for-agents/copilot-session-management/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/navendubrajesh/context-management-for-agents/copilot-session-management"><img src="https://agentmods.dev/badge/skills/navendubrajesh/context-management-for-agents/copilot-session-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00092 | $0.01436 |
| Opus 5 | $0.00046 | $0.00718 |
| Sonnet 5 | $0.00018 | $0.00287 |
| Haiku 4.5 | $0.00009 | $0.00144 |
Grade A, and why
copilot-session-management 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Copilot Session Management
GitHub Copilot CLI holds every user message, model response, tool call, and tool result in a fixed-size context window. This skill covers the operational lifecycle: monitoring usage, compaction, checkpoints, and session hygiene — the levers that keep long-running Copilot sessions coherent.
When to Activate
Activate this skill when:
- A Copilot CLI session is long-running and the agent seems to forget earlier parts of the conversation
- Planning a multi-phase task (scaffold → implement → test → PR) in a single session
- Deciding whether to continue a session, compact proactively, or start fresh
- Debugging contradictions between current agent behavior and earlier decisions
- Auditing what was preserved across a compaction
Do not activate this skill for adjacent work owned by other skills:
- Do not activate for how Copilot builds prompts and retrieves context:
copilot-context-architecture. - Do not activate for designing compression strategies in your own agent systems:
context-compression. - Do not activate for diagnosing attention-level failures:
context-degradation.
Core Concepts
What fills the context window
Four accumulating components:
- System instructions and tool definitions — fixed overhead, always present.
- User messages — every prompt sent.
- Model responses — everything Copilot says back.
- Tool calls and results — both request and output; tool results are often the largest contributor (long file reads, verbose command output).
Monitoring: /context
The /context slash command displays a visual breakdown: System/Tools (fixed overhead), Messages (conversation history), Free Space, and Buffer (reserved portion that triggers automatic management). Use it when a session is long, when Copilot seems forgetful, or to check whether compaction has occurred or is imminent.
Compaction
- Automatic trigger: at ~80% of capacity, compaction starts in the background, leaving a ~20% buffer so tool calls keep running. If context fills to ~95% before compaction finishes, the CLI pauses briefly until it completes.
- Manual trigger:
/compactat any time — useful before starting a new phase of work. Esc cancels. - Mechanism: snapshot the conversation → send the full history to the model with a summarization prompt (capturing goals, work done, key technical details, important files, next steps) → replace history with the summary plus original user instructions and current plan/to-do state → retain messages added during background compaction.
- What is lost: exact wording of messages, full command outputs, minor early decisions. Compaction is summarization — irreversible and lossy. Without it, the only fallback would be silently dropping old messages.
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.
- 11d ago First seen · 88 lines · 92 tokens per session scan A a09a609ec8c2
copilot-session-management is a skill published in the GitHub repository navendubrajesh/context-management-for-agents (2 stars, last pushed 2mo ago), licensed MIT. It adds 92 tokens to every session and 1,436 once invoked, about $0.0005 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 2026-08-31.
Other skills, from other repositories
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.