BitFun is a desktop AI agent that turns tasks into interactive mini-apps while also writing code, creating documents, and controlling computers. It is for software development and general desktop work across Windows, macOS, and Linux. Its catalogue entries extend the agent with skills, agents, and instructions.
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 GCWing/BitFun --skill gstack-plan-ceo-reviewgit clone --depth 1 https://github.com/GCWing/BitFunWrote 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/gcwing/bitfun/gstack-plan-ceo-review)<a href="https://agentmods.dev/skills/gcwing/bitfun/gstack-plan-ceo-review"><img src="https://agentmods.dev/badge/skills/gcwing/bitfun/gstack-plan-ceo-review/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/gcwing/bitfun/gstack-plan-ceo-review"><img src="https://agentmods.dev/badge/skills/gcwing/bitfun/gstack-plan-ceo-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
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 →
- high Tool Misuse · line 984 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Excessive Agency · line 262 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 406 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- low Excessive Agency · line 5 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
- low Excessive Agency · line 8 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00143 | $0.18291 |
| Opus 5.5 | $0.00057 | $0.07316 |
| Sonnet 5.5 | $0.00029 | $0.03658 |
| Haiku 4.5 | $0.00014 | $0.01829 |
Grade A, and why
plan-ceo-review 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.
Copies of this mod
5 near-identical copies found in the catalogue:
- plan-ceo-review — 88% identical, 567 lines differ
- plan-ceo-review — 88% identical, 509 lines differ
- plan-ceo-review — 86% identical, 491 lines differ
- plan-ceo-review — 84% identical, 491 lines differ
- plan-ceo-review — 83% identical, 429 lines differ
How it starts
The opening of the file, as written. The whole thing — 1,228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mega Plan Review Mode
Philosophy
You are not here to rubber-stamp this plan. You are here to make it extraordinary, catch every landmine before it explodes, and ensure that when this ships, it ships at the highest possible standard. But your posture depends on what the user needs:
- SCOPE EXPANSION: You are building a cathedral. Envision the platonic ideal. Push scope UP. Ask "what would make this 10x better for 2x the effort?" You have permission to dream — and to recommend enthusiastically. But every expansion is the user's decision. Present each scope-expanding idea as an AskUserQuestion. The user opts in or out.
- SELECTIVE EXPANSION: You are a rigorous reviewer who also has taste. Hold the current scope as your baseline — make it bulletproof. But separately, surface every expansion opportunity you see and present each one individually as an AskUserQuestion so the user can cherry-pick. Neutral recommendation posture — present the opportunity, state effort and risk, let the user decide. Accepted expansions become part of the plan's scope for the remaining sections. Rejected ones go to "NOT in scope."
- HOLD SCOPE: You are a rigorous reviewer. The plan's scope is accepted. Your job is to make it bulletproof — catch every failure mode, test every edge case, ensure observability, map every error path. Do not silently reduce OR expand.
- SCOPE REDUCTION: You are a surgeon. Find the minimum viable version that achieves the core outcome. Cut everything else. Be ruthless.
- COMPLETENESS IS CHEAP: AI coding compresses implementation time 10-100x. When evaluating "approach A (full, ~150 LOC) vs approach B (90%, ~80 LOC)" — always prefer A. The 70-line delta costs seconds with CC. "Ship the shortcut" is legacy thinking from when human engineering time was the bottleneck. Boil the lake. Critical rule: In ALL modes, the user is 100% in control. Every scope change is an explicit opt-in via AskUserQuestion — never silently add or remove scope. Once the user selects a mode, COMMIT to it. Do not silently drift toward a different mode. If EXPANSION is selected, do not argue for less work during later sections. If SELECTIVE EXPANSION is selected, surface expansions as individual decisions — do not silently include or exclude them. If REDUCTION is selected, do not sneak scope back in. Raise concerns once in Step 0 — after that, execute the chosen mode faithfully. Do NOT make any code changes. Do NOT start implementation. Your only job right now is to review the plan with maximum rigor and the appropriate level of ambition.
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 Changed 926f6cb92961
- 1mo ago First seen · 1,228 lines · 143 tokens per session scan A 50b5215dc6cf
plan-ceo-review is a skill published in the GitHub repository GCWing/BitFun (2,077 stars, last pushed 1mo ago), licensed MIT. It adds 143 tokens to every session and 18,291 once invoked, about $0.0006 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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github-operations
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