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/gcwing/bitfun/gstack-investigatenpx skills add GCWing/BitFun --skill gstack-investigategit clone --depth 1 https://github.com/GCWing/BitFunWhat 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 | $0.00112 | $0.02273 |
| Opus 5 | $0.00056 | $0.01137 |
| Sonnet 5 | $0.00022 | $0.00455 |
| Haiku 4.5 | $0.00011 | $0.00227 |
Grade A, and why
investigate 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 2d 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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Systematic Debugging
Iron Law
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST.
Fixing symptoms creates whack-a-mole debugging. Every fix that doesn't address root cause makes the next bug harder to find. Find the root cause, then fix it.
BitFun Team Mode Dispatch
When this skill is invoked by BitFun Team Mode, this skill supplies the debugging methodology. Use existing Task sub-agents to gather independent evidence, then keep hypothesis selection and fixes in the main Team session.
- Do not assume a Debugger sub-agent exists. Choose only from the Task tool's available agents.
- Prefer matching custom debugging/domain sub-agents if available; otherwise use
Explorefor code-path tracing andFileFinderfor locating logs, configs, tests, and affected files. - Split independent evidence tracks into parallel Task calls when useful: reproduction path, recent-change audit, config/environment audit, and suspected subsystem trace.
- Keep Task work read-only until root cause is proven. Ask for facts, file paths, commands tried, observations, and confidence.
- The main Team orchestrator owns the root-cause statement, fix plan, implementation, and regression test.
Phase 1: Root Cause Investigation
Gather context before forming any hypothesis.
-
Collect symptoms: Read the error messages, stack traces, and reproduction steps. If the user hasn't provided enough context, ask ONE question at a time via AskUserQuestion.
-
Read the code: Trace the code path from the symptom back to potential causes. Use Grep to find all references, Read to understand the logic.
-
Check recent changes:
git log --oneline -20 -- <affected-files>Was this working before? What changed? A regression means the root cause is in the diff.
-
Reproduce: Can you trigger the bug deterministically? If not, gather more evidence before proceeding.
Prior Learnings
Use only BitFun in-session memory, project docs, .bitfun/team/ artifacts, git history, TODO files, and prior design/review artifacts. Do not run external learning or config helpers, and do not ask the user to enable cross-project learning. If a relevant prior artifact is found, cite it as: Prior BitFun context applied: <source>.
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.
- 2d ago First seen · 213 lines · 112 tokens per session scan A 8dcade7abfa8
investigate is a skill published in the GitHub repository GCWing/BitFun (1,871 stars, last pushed 2d ago), licensed MIT. It adds 112 tokens to every session and 2,273 once invoked, about $0.0006 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
git-delegation
将所有 git 操作委托给 Manager 执行。Worker 无法直接访问 git credentials，因此任何需要认证的 git 操作（clone、push、fetch 等）都需要通过此机制委托给 Manager。.
agentteams-migrate
Analyze current OpenClaw setup and generate a migration package (ZIP) for importing into AgentTeams as a managed Worker.
workerflow-internal-workflow
Use when a QwenPaw-backed Worker needs to decide whether to do work directly, use native subagents for internal parallelism, or create a temporary QwenPaw agent with a custom AGENTS.md and skills.
find-skills
Discover and install agent skills from the open ecosystem. Use when you encounter an unfamiliar domain, framework, or workflow that you lack specialized knowledge about, or when your coordinator suggests searching for skills before starting a task.
higress-gateway-management
Manage the Higress AI Gateway via its Console API (consumers, routes, AI providers, MCP servers). Use when creating consumers, configuring routes, or managing AI gateway settings.
worker-management
Use when admin requests hand-creating or resetting a Worker, starting/stopping a Worker, managing Worker skills, enabling peer mentions, or opening a QwenPaw console. Use agentteams-find-worker only as a helper for Nacos-backed market import or when task assignment needs you to discover a suitable Worker.