Memmy is a local memory hub that gives multiple AI agents one shared, persistent context about their user. It helps people continue work across agents such as Claude Code, Codex, OpenClaw, and Hermes Agent. The catalogue entries are skills for using Memmy with supported agents.
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 MemTensor/memmy-agent --skill pdfgit clone --depth 1 https://github.com/MemTensor/memmy-agentWrote 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/memtensor/memmy-agent/pdf)<a href="https://agentmods.dev/skills/memtensor/memmy-agent/pdf"><img src="https://agentmods.dev/badge/skills/memtensor/memmy-agent/pdf/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/memtensor/memmy-agent/pdf"><img src="https://agentmods.dev/badge/skills/memtensor/memmy-agent/pdf.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 | $0.00056 | $0.00564 |
| Opus 5.5 | $0.00022 | $0.00226 |
| Sonnet 5.5 | $0.00011 | $0.00113 |
| Haiku 4.5 | $0.00006 | $0.00056 |
Grade B, and why
pdf scanned grade B with 1 finding 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 25d 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sudo apt-get install -y poppler-utils Copies of this mod
8 near-identical copies found in the catalogue:
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PDF Skill
When to use
- Read or review PDF content where layout and visuals matter.
- Create PDFs programmatically with reliable formatting.
- Validate final rendering before delivery.
Workflow
- Prefer visual review: render PDF pages to PNGs and inspect them.
- Use
pdftoppmif available. - If unavailable, install Poppler or ask the user to review the output locally.
- Use
- Use
reportlabto generate PDFs when creating new documents. - Use
pdfplumber(orpypdf) for text extraction and quick checks; do not rely on it for layout fidelity. - After each meaningful update, re-render pages and verify alignment, spacing, and legibility.
Temp and output conventions
- Use
tmp/pdfs/for intermediate files; delete when done. - Write final artifacts under
output/pdf/when working in this repo. - Keep filenames stable and descriptive.
Dependencies (install if missing)
Prefer uv for dependency management.
Python packages:
uv pip install reportlab pdfplumber pypdf
If uv is unavailable:
python3 -m pip install reportlab pdfplumber pypdf
System tools (for rendering):
# macOS (Homebrew)
brew install poppler
# Ubuntu/Debian
sudo apt-get install -y poppler-utils
If installation isn't possible in this environment, tell the user which dependency is missing and how to install it locally.
Environment
No required environment variables.
Rendering command
pdftoppm -png $INPUT_PDF $OUTPUT_PREFIX
Quality expectations
- Maintain polished visual design: consistent typography, spacing, margins, and section hierarchy.
- Avoid rendering issues: clipped text, overlapping elements, broken tables, black squares, or unreadable glyphs.
- Charts, tables, and images must be sharp, aligned, and clearly labeled.
- Use ASCII hyphens only. Avoid U+2011 (non-breaking hyphen) and other Unicode dashes.
- Citations and references must be human-readable; never leave tool tokens or placeholder strings.
Final checks
- Do not deliver until the latest PNG inspection shows zero visual or formatting defects.
- Confirm headers/footers, page numbering, and section transitions look polished.
- Keep intermediate files organized or remove them after final approval.
What ships with it
1 file 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.
- 25d ago First seen · 68 lines · 56 tokens per session scan B d108cf2b3635
pdf is a skill published in the GitHub repository MemTensor/memmy-agent (2,102 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 564 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-21.
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Nano PDF
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OCR and Documents
Recover text from scanned or image-heavy documents before attempting structured analysis or downstream writing tasks.
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Control browser automation through HTTP API. Supports page navigation, element interaction (click, type, select), data extraction, accessibility snapshot analysis, screenshot, JavaScript execution, and batch operations.