Borrowing it
Nothing to install: this file belongs to swarm-ai-research/swarm. 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/swarm-ai-research/swarm/main/.skills/session-close/SKILL.mdgit clone --depth 1 https://github.com/swarm-ai-research/swarmWrote 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/swarm-ai-research/swarm/session-close)<a href="https://agentmods.dev/skills/swarm-ai-research/swarm/session-close"><img src="https://agentmods.dev/badge/skills/swarm-ai-research/swarm/session-close.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.00508 |
| Opus 5 | $0.00019 | $0.00254 |
| Sonnet 5 | $0.00008 | $0.00102 |
| Haiku 4.5 | $0.00004 | $0.00051 |
Grade A, and why
session-close 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 4d 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.
What it actually says
EXECUTE NOW
Run all steps sequentially. Do not skip any step.
Step 1: Inventory changes
git status
git diff --stat
List all modified, added, and deleted files.
Step 2: Summarize the session
Answer these questions by reviewing the conversation history and current state:
- What changed? — files modified, runs completed, claims updated
- What did we learn? — key findings, surprises, pattern changes
- What's next? — the most valuable next experiment or task
- What should I remember? — decisions made, preferences expressed, context that would be lost
Step 3: Update memory
Update .letta/memory/threads/research-log.md
Append a session entry:
## {date} — {session focus}
**Ran:** {experiments or tasks completed}
**Found:** {key results}
**Learned:** {insights}
**Next:** {next steps}
**Run pointers:** {run_ids if any}
Update .letta/memory/threads/current.md
Replace the content with:
- Current hypothesis (carried forward or updated)
- What we're testing next
- This session's summary (moved to "Last session summary")
- Next experiment
- Any blockers
Update .letta/memory/runs/latest.md
Add any new run pointers to the table.
Step 4: Commit and push
git add <changed files> # stage code changes
bd sync # sync beads
git commit -m "<summary>" # commit with descriptive message
bd sync # sync any new beads changes
git push # push to remote
Step 5: Confirm
Print:
Session closed.
Summary: {one-line summary}
Memory updated: threads/current.md, threads/research-log.md
Committed: {commit hash}
Pushed: {branch}
Next session: {what to do first}
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.
- 4d ago First seen · 86 lines · 38 tokens per session scan A 52027ac792e9
session-close is a skill published in the GitHub repository swarm-ai-research/swarm (41 stars, last pushed today), licensed MIT. It adds 38 tokens to every session and 508 once invoked, about $0.0002 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 2026-09-03.
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