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 Bilal140202/the-lord-of-the-skills --skill kingdaddy007__my-osgit clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-skillsWrote 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/bilal140202/the-lord-of-the-skills/kingdaddy007__my-os)<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/kingdaddy007__my-os"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/kingdaddy007__my-os/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/bilal140202/the-lord-of-the-skills/kingdaddy007__my-os"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/kingdaddy007__my-os.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 | $0.00040 | $0.00700 |
| Opus 5.5 | $0.00016 | $0.00280 |
| Sonnet 5.5 | $0.00008 | $0.00140 |
| Haiku 4.5 | $0.00004 | $0.00070 |
Grade A, and why
Context Hygiene & 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 1mo 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 — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Hygiene & Session Management
Purpose
AI context windows degrade as conversations grow. After ~30+ exchanges, the AI loses track of earlier constraints, starts hallucinating details, and wastes tokens re-reading irrelevant history.
This skill teaches Anti-Gravity to actively manage session boundaries automatically — securing all progress to disk before the user moves to a clean chat window.
When to Advise a Session Split
Recommend the user open a new chat window when:
- The task changes significantly. If we finished debugging and are now building a new feature, that is a new session.
- The conversation exceeds ~30 exchanges. Context quality degrades. Proactively say: "We've covered a lot. I recommend starting a fresh chat for the next piece so I stay sharp."
- Multiple unrelated tasks are being discussed. Each task deserves its own clean context.
- A micro-task sequence is complete. After finishing a planned set of tasks, suggest: "Good stopping point. For the next batch, a fresh session will give you better results."
How to Execute a Handoff (The Zero-Friction Method)
Never ask Beloved to manually copy-paste a "Handoff Brief." Instead, perform these two steps automatically:
Step 1: Secure Long-Term Knowledge (Memory)
Before suggesting a split, ensure all permanent knowledge from this session is written to disk:
- Did we make an architectural choice? Write it to
.agents/memory/decisions-log.md. - Did we learn what not to do? Write it to
.agents/memory/mistakes-to-avoid.md. - Did we establish a new convention? Write it to
.agents/memory/common-patterns.md.
Step 2: Secure Immediate State (Workflow)
Update .agents/workflow-state.json so the next session knows exactly where to resume.
Ensure the notes, key_decisions, and phases fields are perfectly up to date.
Reference format from GLOBAL_MEMORY.md:
{
"workflow": "build-feature",
"current_phase": "IMPLEMENT",
"completion_pct": 64,
"notes": "Finished the UI layout. Next session must focus on wiring the submit button to the API.",
"key_decisions": ["Used Flexbox instead of Grid for the main container"],
"blockers": []
}
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.
- 1mo ago First seen · 66 lines · 40 tokens per session scan A b5984b88a12d
Context Hygiene & Session Management is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 700 once invoked, about $0.0002 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
aider-1h-ttl
Aider uses 5min TTL by default and works around long pauses with keepalive pings. Wire up the 1h TTL beta instead.
serpsmith
Publish SEO articles, verify unattended health, and gate source-to-runtime releases.
agent-memory
Persistent memory system for AI coding agents. Use when you need to save facts about the user, store interaction preferences, log session events, or search previously saved memories. Triggers on remembering, saving context, recalling past decisions, or when the user says "remember this". Also use proactively when the…
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as reportlab, pdfplumber, and pypdf for generation and extraction.
archive
Archives every closed period still in the log: one summary per period, distils durable facts into memory (propose-then-confirm), resets log.md. Period follows work.archivecadence (weekly, bi-weekly, monthly, quarterly, yearly). Trigger: "/archive", "archive", "archive week", "archive month", "week wrap-up".
agents-meet-rl
Troubleshooter for agentic-RL training, evaluation, and experiment design on LLM agents (single or multi-agent, multi-turn, tool-augmented). Routes a user's symptom to fixes anchored in the corpus. TRIGGER when: user is training, evaluating, or designing experiments for an RL-trained LLM agent; symptoms like reward…