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 luabagg/agent-skills --skill agentfolio-operatorgit clone --depth 1 https://github.com/luabagg/agent-skillsWrote 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/luabagg/agent-skills/agentfolio-operator)<a href="https://agentmods.dev/skills/luabagg/agent-skills/agentfolio-operator"><img src="https://agentmods.dev/badge/skills/luabagg/agent-skills/agentfolio-operator/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/luabagg/agent-skills/agentfolio-operator"><img src="https://agentmods.dev/badge/skills/luabagg/agent-skills/agentfolio-operator.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 | $0.00033 | $0.00639 |
| Opus 5.5 | $0.00013 | $0.00256 |
| Sonnet 5.5 | $0.00007 | $0.00128 |
| Haiku 4.5 | $0.00003 | $0.00064 |
Grade A, and why
agentfolio-operator 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 5d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agentfolio Operator
Agentfolio orchestrates collection.yaml. This repository's adapter owns harness behavior. Do not hand-edit live harness configuration when a declared action exists.
Start with the collection
Run these commands from the collection checkout (or set AGENTFOLIO_COLLECTION):
agentfolio doctor --collection .
agentfolio list harnesses --collection .
agentfolio plan --collection .
Agentfolio also discovers the nearest collection.yaml or uses AGENTFOLIO_COLLECTION.
Profiles
| Intent | Profile |
|---|---|
| Personal + curated skills and global instructions | default |
| Personal skills only | skills |
| Personal skills plus Pi configuration | pi |
| Committed Pi model lock and Scope only | pi-catalog |
| Personal skills plus Cursor agents | cursor |
| Personal skills plus OpenCode plugins and agents | opencode |
| Personal skills plus global, Pi, Cursor, and OpenCode | all |
Preview before applying:
agentfolio plan --profile pi
agentfolio apply --profile pi --dry-run
agentfolio apply --profile pi-catalog --dry-run
agentfolio apply --profile pi
Collection-owned model commands
agent-skills implements model discovery and generated catalog files, not Agentfolio core:
agent-skills models check
agent-skills models diff
agent-skills models refresh
Edit harnesses/catalog.yaml. The generated model lock is an output. Run models check, then preview with models diff. Use models refresh only when the policy and discovery results are ready to commit. Apply Pi changes through agentfolio apply --profile pi --dry-run.
Decision rules
- Change workflow intent in
collection.yaml. Change execution semantics inscripts/agentfolio-adapter.mjsor the relevant setup script. - Use
agentfolio list harnesses,plan,doctor, andverifyfor inspection. - Treat direct
agent-skills setup|installcommands as adapter implementations or debugging surfaces. - Keep credentials outside the collection. Never copy OAuth tokens, API keys, or login state.
- Dry-run first unless the user explicitly requests an immediate apply.
- Stop on the first failed action and preserve unmanaged user configuration.
- Restart a harness when its extensions or providers changed.
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.
- 5d ago Changed d10442f149bc
- 1mo ago Changed · +8 lines 238c0ac28886
- 1mo ago First seen · 68 lines · 33 tokens per session scan A 347c01598713
agentfolio-operator is a skill published in the GitHub repository luabagg/agent-skills (3 stars, last pushed today), licensed MIT. It adds 33 tokens to every session and 639 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
harness
Connect this Bankr account to the user's Harness account (tryharness.ai) and manage everything Harness-side from here. Pair with a signed wallet proof, then inspect the Harness trading wallet and portfolio, fund it on the user's request, request withdrawals back to this wallet, buy Harness credits with $HARNESS over…
web-ui-motion
Build polished front-end UI together with a signature motion effect in a single self-contained HTML file, combining SVG.js / SVG filters and the Canvas 2D API. Use when the user asks to build a web page, landing page, dashboard, or component that has a special visual effect, animation, particle system, fluid/water…
openspec-propose
Create a complete OpenSpec proposal with design, specs, prototype, and tasks. Use when the user wants a change ready for implementation.
prototype-workflow
Generate and lifecycle-manage HTML prototypes for UI exploration and OpenSpec changes. Use when creating, validating, completing, or archiving a UI prototype.
html-output
Produce rich, self-contained, single-file HTML as the default output format instead of Markdown — for specs, plans, code reviews, PR write-ups, reports, explainers, design explorations, slide decks, SVG diagrams, and small interactive editors with copy-as-prompt/JSON export. USE WHEN the user asks to "make an HTML…
harness-engineering-guide
Audit, design, and implement AI agent harnesses for any codebase. A harness is the constraints, feedback loops, and verification systems surrounding AI coding agents — improving it is the highest-leverage way to improve AI code quality. Three modes: Audit (scorecard), Implement (set up components), Design (full…