Memoh is an open-source multi-agent platform that gives each AI agent a persistent computer-like workspace with a filesystem, desktop, browser, network access, and long-term memory. It is for individuals and teams running agents continuously, including built-in agents or coding agents such as Claude Code and Codex, through chat platforms and a web interface.
Borrowing it
Nothing to install: this file belongs to felinics/Memoh. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/felinics/Memoh/main/.agents/skills/memoh-error-handling/SKILL.mdgit clone --depth 1 https://github.com/felinics/MemohWrote 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/felinics/memoh/memoh-error-handling)<a href="https://agentmods.dev/skills/felinics/memoh/memoh-error-handling"><img src="https://agentmods.dev/badge/skills/felinics/memoh/memoh-error-handling/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/felinics/memoh/memoh-error-handling"><img src="https://agentmods.dev/badge/skills/felinics/memoh/memoh-error-handling.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Data Exfiltration · line 91 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00092 | $0.03053 |
| Opus 5.5 | $0.00037 | $0.01221 |
| Sonnet 5.5 | $0.00018 | $0.00611 |
| Haiku 4.5 | $0.00009 | $0.00305 |
Grade A, and why
memoh-error-handling scanned grade A 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 28d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -si -X POST $HOST/bots -H "Authorization: Bearer $T" -H 'Content-Type: application/json' \ The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
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.
- 28d ago Changed · +5 lines ba5dbcd96ef6
- 29d ago Changed · +16 lines d387b1e0e1bd
- 2mo ago First seen · 120 lines · 92 tokens per session scan A 6f6aa9ee18a2
memoh-error-handling is a skill published in the GitHub repository felinics/Memoh (2,785 stars, last pushed yesterday), licensed AGPL-3.0. It adds 92 tokens to every session and 3,053 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
memoh-error-handling compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| memoh-error-handlingfelinics/Memoh | Skill | 2.8k | yesterday | AGPL-3.0 | A | 92 | Claude Code, Codex |
| claude-apispytensor/openmozi | Skill | 441 | 3mo ago | MIT | A | 294 | Claude Code |
| blind-sqliPurpleAILAB/Decepticon | Skill | 6.5k | 8d ago | Apache-2.0 | A | 88 | Claude Code, Codex |
| race-conditionPurpleAILAB/Decepticon | Skill | 6.5k | 8d ago | Apache-2.0 | A | 80 | Claude Code, Codex |
| groq-inferencesynthetic-sciences/openscience | Skill | 4.3k | 2d ago | Apache-2.0 | A | 77 | Claude Code, Codex |
| api-server-sent-eventsPurpleAILAB/Decepticon | Skill | 6.5k | 8d ago | Apache-2.0 | A | 54 | Claude Code |
| golang-graphqlsamber/cc-skills-golang | Skill | 3.8k | 5d ago | MIT | A | 77 | Claude Code |