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 ThinkfleetAI/memmesh --skill tourgit clone --depth 1 https://github.com/ThinkfleetAI/memmeshWrote 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/thinkfleetai/memmesh/tour)<a href="https://agentmods.dev/skills/thinkfleetai/memmesh/tour"><img src="https://agentmods.dev/badge/skills/thinkfleetai/memmesh/tour/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/thinkfleetai/memmesh/tour"><img src="https://agentmods.dev/badge/skills/thinkfleetai/memmesh/tour.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00046 | $0.00261 |
| Opus 5.5 | $0.00018 | $0.00104 |
| Sonnet 5.5 | $0.00009 | $0.00052 |
| Haiku 4.5 | $0.00005 | $0.00026 |
Grade A, and why
tour 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.
What it actually says
tour
Show the full contents of memory, organized.
Pull the set
{ "name": "memory_list", "arguments": { "projectId": "<repo>", "limit": 100 } }
For a personal overview, pass userId and scope: "user" instead.
Present it
Group by type (preference / fact / rule / decision / behavior_pattern / …),
then within each show content with a short id prefix. Call out anything
status: superseded separately so the user sees what's been replaced.
End with a one-line summary: total count and the type breakdown (that's exactly
what the stats skill returns if you want the numbers).
Big memory sets
If memory_list hits the limit, page with offset, or narrow by scope /
type. Suggest dream (consolidation) if the tour reveals lots of duplicates
or contradictions.
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 · 33 lines · 46 tokens per session scan A 622242cd5ff7
tour is a skill published in the GitHub repository ThinkfleetAI/memmesh (405 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 46 tokens to every session and 261 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 2026-08-30.
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