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 agentmods add skills/thinkfleetai/memmesh/peeknpx skills add ThinkfleetAI/memmesh --skill peekgit 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/peek)<a href="https://agentmods.dev/skills/thinkfleetai/memmesh/peek"><img src="https://agentmods.dev/badge/skills/thinkfleetai/memmesh/peek.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 | $0.00050 | $0.00252 |
| Opus 5 | $0.00025 | $0.00126 |
| Sonnet 5 | $0.00010 | $0.00050 |
| Haiku 4.5 | $0.00005 | $0.00025 |
Grade A, and why
peek 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 4d 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
peek
Fast, low-noise lookup.
By query
{ "name": "memory_search", "arguments": { "query": "<term>", "projectId": "<repo>", "limit": 8 } }
Render each hit as a single line: [id-prefix] content — scope/type. Don't dump
full JSON.
By id
{ "name": "memory_recall", "arguments": { "id": "<id>" } }
memory_recall also bumps recency (marks the item recently used). Use it to
resolve a [memmesh:<id>] citation to its full content.
When to escalate
If the user wants everything grouped by category, use tour. If they want a
synthesized picture of one subject (profile + patterns + predictions), use
context-loader / memory_build_context.
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.
- 4d ago First seen · 32 lines · 50 tokens per session scan A 8ebaa7b98a9a
peek is a skill published in the GitHub repository ThinkfleetAI/memmesh (440 stars, last pushed 9d ago), licensed Apache-2.0. It adds 50 tokens to every session and 252 once invoked, about $0.0003 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.
Other skills, from other repositories
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brainstorming
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auto-perf-optimize
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…