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 kimtth/agent-skill-100-lines-or-less --skill agent-memorygit clone --depth 1 https://github.com/kimtth/agent-skill-100-lines-or-lessWrote 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/kimtth/agent-skill-100-lines-or-less/agent-memory)<a href="https://agentmods.dev/skills/kimtth/agent-skill-100-lines-or-less/agent-memory"><img src="https://agentmods.dev/badge/skills/kimtth/agent-skill-100-lines-or-less/agent-memory.svg" alt="Measured on agentmods" 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 | $0.00028 | $0.00334 |
| Opus 5 | $0.00014 | $0.00167 |
| Sonnet 5 | $0.00006 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00033 |
Grade A, and why
agent-memory 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 8d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 8d ago First seen · 34 lines · 28 tokens per session scan A 96cb441b80b0
agent-memory is a skill published in the GitHub repository kimtth/agent-skill-100-lines-or-less (2 stars, last pushed 2mo ago), with no licence file. It adds 28 tokens to every session and 334 once invoked, about $0.0001 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
iblai-api-agent-memory
Manage an ibl.ai agent's memories via the platform API — list and filter agent (mentor) memories (by category, user, email, date), curate global (cross-agent) memories, curate shared agent knowledge injected into every user's chat, add/edit/delete memories, manage memory categories, and toggle capture/recall settings.…
workspace-knowledge-sync
Syncs knowledge to the agentic-harness knowledge base and AGENTS.md learned facts. Use when the assistant discovers new patterns, learns user preferences, workspace facts, or identifies information worth preserving for future sessions. Integrates with platform-engineer (formerly tech-assistant) for automatic trigger…
workspace
Scaffold and manage the stateless AI workspace — context, packs, repos, and knowledge for multi-repo orchestration.
iblai-api-agent-history
Read an ibl.ai agent's conversation history and summaries via the platform API — list conversations with sentiment/topic/user/date filters, get general summaries and per-conversation memory, and export chat history as an async report. Use when reviewing or exporting how users have chatted with an agent.
tellonce
EVERY-MESSAGE enforcement: scan for preference/pitfall/friction signals, record to memory, log observations. Also handles memory audit/restructure. Use on EVERY user message — even simple ones, even during intensive technical work, even when you think there's nothing to detect. If you're not invoking this, you're…
tellonce
Use when handling any user message; records and enforces user preferences with Codex-native audit/wrapper support.