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/fmagent-project/fm-agent-plugin/installnpx skills add fmagent-project/FM-Agent-Plugin --skill installgit clone --depth 1 https://github.com/fmagent-project/FM-Agent-PluginWrote 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/fmagent-project/fm-agent-plugin/install)<a href="https://agentmods.dev/skills/fmagent-project/fm-agent-plugin/install"><img src="https://agentmods.dev/badge/skills/fmagent-project/fm-agent-plugin/install.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 | $0.00039 | $0.00828 |
| Opus 5 | $0.00019 | $0.00414 |
| Sonnet 5 | $0.00008 | $0.00166 |
| Haiku 4.5 | $0.00004 | $0.00083 |
Grade A, and why
FM-Agent-Install 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 3d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Install FM-Agent framework to the plugin data directory for automated code reasoning and bug detection.
Overview
This skill clones FM-Agent from the official repository to the plugin data directory $HOME/.fm-agent-plugin/. FM-Agent is a framework that realizes fully automated reasoning for large-scale systems using LLM-based Hoare-style verification.
Installation Steps
For the following steps, exactly execute the provide bash commands. Do not run other commands or modify the provided commands.
If any step fails, stop the installation and inform the user to set up FM-Agent manually.
Step 1: Ensure Plugin Data Directory Exists
Create $HOME/.fm-agent-plugin/ if it does not already exist (mkdir -p is a no-op when the directory is present):
mkdir -p $HOME/.fm-agent-plugin/
If mkdir fails (for example, due to permission errors), stop the installation and inform the user to set up FM-Agent manually.
Step 2: Clone or Update FM-Agent
Clone FM-Agent to $HOME/.fm-agent-plugin/FM-Agent. If it already exists, preserve the local checkout because this installation may include local CLI backend patches:
if [ -d "$HOME/.fm-agent-plugin/FM-Agent" ]; then
echo "FM-Agent already exists; preserving local checkout and patches."
else
echo "Cloning FM-Agent..."
cd "$HOME/.fm-agent-plugin/" && git clone https://github.com/fmagent-project/FM-Agent.git
fi
Step 3: Create Local CLI Backend Configuration
Create $HOME/.fm-agent-plugin/FM-Agent/.env if needed, then ensure backend keys are present. The default remains FM_AGENT_MODEL_BACKEND=opencode, matching upstream FM-Agent. Users can switch to auto, codex-cli, or claude-cli when they want local CLI model execution. Empty LLM_EFFORT omits the effort flag.
cd "$HOME/.fm-agent-plugin/FM-Agent" && { [ -f .env ] || cp .env.example .env; } && \
grep -q '^FM_AGENT_MODEL_BACKEND=' .env || printf '\nFM_AGENT_MODEL_BACKEND=opencode\n' >> .env && \
grep -q '^LLM_EFFORT=' .env || printf 'LLM_EFFORT=\n' >> .env
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.
- 3d ago First seen · 94 lines · 39 tokens per session scan A 2e7061871c8f
FM-Agent-Install is a skill published in the GitHub repository fmagent-project/FM-Agent-Plugin (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 828 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
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…