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 pyros-projects/limitless --skill memory-close-sessiongit clone --depth 1 https://github.com/pyros-projects/limitlessWrote 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/pyros-projects/limitless/memory-close-session)<a href="https://agentmods.dev/skills/pyros-projects/limitless/memory-close-session"><img src="https://agentmods.dev/badge/skills/pyros-projects/limitless/memory-close-session/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/pyros-projects/limitless/memory-close-session"><img src="https://agentmods.dev/badge/skills/pyros-projects/limitless/memory-close-session.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 | $0.00066 | $0.02334 |
| Opus 5.5 | $0.00026 | $0.00934 |
| Sonnet 5.5 | $0.00013 | $0.00467 |
| Haiku 4.5 | $0.00007 | $0.00233 |
Grade A, and why
memory-close-session 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 yesterday.
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 — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Close Session
BETA — This memory system is in active testing. If you encounter bugs, confusing behavior, or have suggestions, run:
codies-memory feedback "describe what happened" --agent <name>— your feedback is saved and reviewed.
When To Use
At the end of every work session.
What It Does
- Decide on a reflection and a dream, and write the ones that pass their test (see "Reflection at Sign-Off" and "Dream at Sign-Off" below). Neither is ever skipped silently: the summary names each one or the reason it was skipped. After a new one, choose your five favorites of that kind again.
- Write session summary with
next_step, the session's moments, and the reflection and dream decisions - Review inbox items older than 7 days
- Enforce 14-day inbox aging rule (promote, compact, or discard stale items)
- Update project active context
- Evaluate pending promotions
- Rebuild warm summaries so the next boot sees updated project summaries and recent episodes
How To Run
Run the installed CLI from the user's project directory. For setup or PATH issues, see INSTALL.md. Fill in the agent name and today's date below.
AGENT="your-agent-name"
TODAY="YYYY-MM-DD"
First decide on the reflection and the dream ("Reflection at Sign-Off" and "Dream at Sign-Off" below) and write the ones that pass their test, so the summary can name them or the reason each was skipped.
# 1. Write session summary (after the reflection and dream decisions)
codies-memory create session \
--agent "$AGENT" \
--title "Session Summary - $TODAY" \
--short "one-line summary of the session" \
--body "## What Happened\n- [describe what was done]\n\n## Decisions Made\n- [list decisions]\n\n## Moments\n- [see Moments below, or none]\n\n## Reflection and Dream\n- Reflection: [RF id, or skipped: one-line reason]\n- Dream: [DR id, or skipped: one-line reason]\n\n## Next Step\n- [what the next session should pick up]" \
--field mode=implement \
--field next_step="[what to do next]"
# This automatically appends to the global daily log. If no named project vault
# resolves, the session lands in the reserved _general project vault.
# Inside Claude Code or Codex the record links itself to this session's
# transcript, so the next boot knows the session is covered.
# 2. Check inbox aging and status
codies-memory status --agent "$AGENT"
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday Changed 4b39a69cd8b0
- 3d ago Changed · +58 lines · +8 tokens per session 7b50b0f844a3
- 8d ago Changed · +34 lines 5d2af954d3b5
- 22d ago Changed · -4 lines 8584dd0ff352
- 1mo ago First seen · 128 lines · 58 tokens per session scan A 9aa17a17db3e
memory-close-session is a skill published in the GitHub repository pyros-projects/limitless (2 stars, last pushed yesterday), licensed MIT. It adds 66 tokens to every session and 2,334 once invoked, about $0.0003 per session on Opus 5.5. 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
Vizra ADK Memory System
Implement persistent memory, session context, and vector memory (RAG) for AI agents.
nav-compact
Clear conversation context while preserving knowledge via context marker. Use when user says "clear context", "start fresh", "done with this task", or when approaching token limits.
adr-ops
Author, index, and lint Architecture Decision Records — append-only memory that recovers the WHY behind a system's shape. Triggers on: adr, architecture decision record, decision log, record this decision, supersede an adr, why was this decided, adr template, next adr number.
hive-mind-advanced
Queen-led collective-intelligence coordination with consensus mechanisms and persistent shared memory. Use when orchestrating a large swarm of agents under a lead coordinator, building consensus across agents, or maintaining durable cross-agent memory.
creator-productivity
Task management and workspace memory for creative work sessions. Manages a TASKS.md file for project tracking, a two-tier memory system (CREATOR.md + creator-memory/), and a daily sprint structure. Use when organizing creative projects, tracking content tasks, or starting a focused work session.
memory-prune
Manual reviewable prune of stale memory entries. Lists project entries older than 30 days with content preview; Frank decides per-entry [keep | archive | pin]. Keeps MEMORY.md under the auto-load 200-line truncation. Use when MEMORY.md exceeds 180 lines or session-end after a heavy work week.