Borrowing it
Nothing to install: this file belongs to ToruAI/megg. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ToruAI/megg/main/.claude/skills/megg-state/SKILL.mdgit clone --depth 1 https://github.com/ToruAI/meggWrote 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/toruai/megg/megg-state)<a href="https://agentmods.dev/skills/toruai/megg/megg-state"><img src="https://agentmods.dev/badge/skills/toruai/megg/megg-state/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/toruai/megg/megg-state"><img src="https://agentmods.dev/badge/skills/toruai/megg/megg-state.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 | $0.00012 | $0.00322 |
| Opus 5 | $0.00006 | $0.00161 |
| Sonnet 5 | $0.00002 | $0.00064 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
megg-state 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 10d 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.
This is a copy
89% identical to megg-state — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Session State Management
Capture or manage session state for cross-session handoff.
Process
Default (no argument) - Capture State
- Review what was worked on in this session
- Summarize into this format:
## Working On
[One-liner: the main task/goal]
## Progress
- [What's been done]
- [Current status]
## Next
- [Immediate next steps]
## Context
[Relevant files, blockers, pending decisions - keep brief]
-
Call the
mcp__megg__statetool with the content:mcp__megg__state({ content: "<formatted content>" }) -
Confirm to user that state was saved
clear - Clear State
- Call
mcp__megg__state({ status: "done" }) - Confirm state was cleared
show - Display Current State
- Call
mcp__megg__state()with no arguments - Display the current state or "No active state"
Notes
- State is ephemeral - overwritten each session
- Auto-expires after 48 hours or when marked done
- Hard limit of 2k tokens to prevent bloat
- Keep content concise and actionable
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.
- 10d ago First seen · 60 lines · 12 tokens per session scan A 4a29c90e8113
megg-state is a skill published in the GitHub repository ToruAI/megg (5 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 322 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to megg-state, differing in 2 lines, and is treated as a copy.
Other skills, from other repositories
memory-audit
An entry point for reviewing and maintaining an AI agent's stored memories. It describes how to remove repetition, preserve useful reasoning, and update memories when old conclusions no longer fit.
memory-audit-discoverability
A review guide for checking whether stored memories can be found at the right time. It focuses on where memories are attached, when they are triggered, whether aliases are missing, and whether a parent has too many children.
memory-audit-belief-duel
A guided review process for conflicting beliefs or memories. It examines cases where two conclusions cannot both be true, including conflicts between a general rule and a more specific memory.
memory-audit-node-decomposition
A method for splitting an oversized knowledge note into smaller notes, each focused on one independent idea. It also explains how to keep useful core information in the original note.
memory-audit-pattern-extraction
A method for investigating repeated mistakes by comparing related memories and checking whether an earlier reminder failed. It looks at where the reminder was stored, when it was created, and whether it was strong enough to prevent the mistake.
memory-audit-dead-data-purge
A review process for identifying memories that do not change future actions. It tests whether a note contains useful, experience-based guidance or only sounds meaningful without affecting decisions.