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 agentmods add skills/pyros-projects/limitless/memory-close-sessionnpx skills add pyros-projects/limitless --skill memory-close-sessiongit clone --depth 1 https://github.com/pyros-projects/limitlessWhat 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 | $0.00058 | $0.01171 |
| Opus 5 | $0.00029 | $0.00585 |
| Sonnet 5 | $0.00012 | $0.00234 |
| Haiku 4.5 | $0.00006 | $0.00117 |
Grade A, and why
memory-close-session scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Close Session
BETA — This memory system is in active testing. If you encounter bugs, confusing behavior, or have suggestions, run:
codies-memory feedback "describe what happened"— your feedback is saved and reviewed.
When To Use
At the end of every work session.
What It Does
- Write session summary with
next_step - Optionally write a dream (see "Dream at Sign-Off" below)
- Review inbox items older than 7 days
- Enforce 14-day inbox aging rule (promote, compact, or discard stale items)
- Update project active context
- Evaluate pending promotions
- Rebuild warm summaries so the next boot sees updated project summaries and recent episodes
How To Run
# 1. Write session summary
AGENT="your-agent-name"
TODAY="$(python - <<'PY'
from datetime import date
print(date.today().isoformat())
PY
)"
codies-memory create session \
--agent "$AGENT" \
--title "Session Summary - $TODAY" \
--short "one-line summary of the session" \
--body "## What Happened\n- [describe what was done]\n\n## Decisions Made\n- [list decisions]\n\n## Next Step\n- [what the next session should pick up]" \
--field mode=implement \
--field next_step="[what to do next]"
# This automatically appends to the global daily log. If no named project vault
# resolves, the session lands in the reserved _general project vault.
# 2. Check inbox aging and status
codies-memory status --agent "$AGENT"
# 3. Run promotion evaluation
uv run python -c "
from codies_memory.records import list_records
from codies_memory.promotion import evaluate_for_promotion
from codies_memory.vault import resolve_global_vault, resolve_project_vault
from pathlib import Path
agent = 'your-agent-name'
global_vault = resolve_global_vault(agent)
project_vault = resolve_project_vault(global_vault, Path.cwd())
if project_vault is None:
print(f'No named project vault found for {Path.cwd()}; skipping project promotion evaluation.')
else:
for rtype in ['inbox', 'thread']:
items = list_records(project_vault, rtype, scope='project', status='active')
for item in items:
result = evaluate_for_promotion(item, context={'session_count': 1})
if result['eligible']:
print(f' Promote {rtype}: {item[\"frontmatter\"][\"title\"][:60]}')
"
# 4. Refresh warm summaries
codies-memory refresh --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.
- 2d 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 (9 stars, last pushed 20d ago), licensed MIT. It adds 58 tokens to every session and 1,171 once invoked, about $0.0003 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
expansion-grant-guard
YAML-based delegation grant ledger — issues, validates, and tracks scoped permission grants for sub-agent expansions with token budgets and auto-expiry.
create-skill
Scaffolds and validates new superpowers skills. Use when creating a new skill for this repository.
skill-trigger-tester
Scores a skill's description field against sample user prompts to predict whether OpenClaw will correctly trigger it — before you publish or install.
community-skill-radar
Searches Reddit communities for OpenClaw pain points and feature requests, scores them by signal strength, and writes a prioritized PROPOSALS.md for you to review and act on.
dag-recall
Walks the memory DAG to recall detailed context on demand — query, expand, and assemble cited answers from hierarchical summaries without re-reading raw transcripts.
memory-dag-compactor
Builds hierarchical summary DAGs from MEMORY.md with depth-aware prompts — leaf summaries preserve detail, higher depths condense to durable arcs, preventing information loss during compaction.