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 matteotitta/genesys-skills --skill learngit clone --depth 1 https://github.com/matteotitta/genesys-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/matteotitta/genesys-skills/learn)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/learn"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/learn/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/matteotitta/genesys-skills/learn"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/learn.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Memory Poisoning · line 64 Skill injects content designed to persist in agent memory or context across interactions. Persistent injection can alter agent behavior long after the initial interaction.Fix: Do not allow untrusted input to persist in agent memory or context. Validate all content before storing and implement memory isolation between sessions.
- medium Excessive Agency · line 328 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00074 | $0.03845 |
| Opus 5 | $0.00037 | $0.01922 |
| Sonnet 5 | $0.00015 | $0.00769 |
| Haiku 4.5 | $0.00007 | $0.00384 |
Grade A, and why
learn 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 12d 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 — 332 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/learn — absorb source material into the knowledge base
Process raw material into structured context. Classify it, extract what matters, file it where it belongs, and connect it to what already exists.
/steal takes from the outside. /learn absorbs from the inside.
Triggers
Invoke when user says:
/learn [file path or URL]/learn --queue(drain mode — see below)- "process this transcript"
- "add this to context"
- "learn from this [call / doc / article / page]"
- "I have a new [transcript / competitor page / doc] — file it"
Do NOT invoke when:
- User wants to extract marketing patterns from external work (use
/steal) - User wants to run a full structured research workflow (use
/company-context,/competitor-research,/icp-research) - User wants to save content they admire (use
/steal→ swipe file) - User wants to analyze a transcript for specific deliverables (use
/transcript-analysis)
--queue mode (drain the slack-capture-bot queue)
When invoked as /learn --queue with no URL/file argument:
-
Inventory the queue. Read
.claude/queue/*.md. Filter to files where frontmatter hasintent: learnANDstatus: unprocessed. If none, say "queue is empty for /learn" and exit. -
Show the user the drain plan before starting. Print a one-line summary per file:
<filename>—<source>— captured<captured_at>— reflex:<reflex>Ask: "Process all N? [y/N/select]" —selectlets the user pick a subset by number.
-
Process serially. For each approved file:
- Read the source URL/path from frontmatter
- Run the standard /learn workflow against that source (classify → extract → file)
- Use the reflex from the queue file as context for "why this was saved"
- At the standard /learn review gate (Gate 1 — quick review), gate per-file
- After completion, mark the queue file:
status: processedprocessed_at: <ISO timestamp>processed_to: <path where /learn deposited the output>
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.
- 12d ago First seen · 332 lines · 74 tokens per session scan A 142f90a09828
learn is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 74 tokens to every session and 3,845 once invoked, about $0.0004 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 2026-08-30.
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mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
resume
Load context from permanent memory and recent session logs. Tiered loading — CLAUDE.md full, session logs frontmatter-only by default.
semantic-search
Zero-dependency TF-IDF search across MUSE memory, roles, and skills. Use when user wants to find information across their project context.