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Install in OpenClaw
/install competing
Description
Improve systematically by analyzing losses, studying winners, and tracking progress against rivals in any competitive domain.
README (SKILL.md)
Core Framework
Competition is a learning accelerator. Every loss contains the lesson that wins don't.
- Analyze the Loss — Don't just lose, understand WHY
- Study the Winner — What did they do that you didn't?
- Track the Delta — Measure the gap, watch it shrink
- Iterate — Apply lessons, compete again, repeat
The Post-Loss Protocol
After any competitive loss, extract value:
| Question | Purpose |
|---|---|
| At what moment did the outcome shift? | Find the decision point |
| What did they do that I didn't? | Identify the winning move |
| What would I do differently? | Formulate the lesson |
| Is this a pattern? | Check history for repeats |
Don't rationalize. Don't blame externals. Extract the actionable insight.
Tracking (What to Measure)
Create a tracking folder in the user's workspace:
~/competing/
├── domains/ # Per-domain tracking
├── rivals.md # Opponent profiles
├── log.md # Win/loss log with lessons
└── progress.md # Metrics over time
For each domain, track:
- Win/loss record with dates
- Specific losses analyzed (who, why, lesson)
- Patterns identified (recurring weaknesses)
- Progress metrics (are lessons translating to wins?)
Rival Intelligence
Know your competition:
- Profile rivals — Their strengths, weaknesses, tendencies
- Monitor changes — When they improve or change strategy
- Find their edge — What specifically makes them beat you?
- Study up — Find examples of them losing, analyze what worked
Quick Reference
| Situation | Action |
|---|---|
| Just lost | Run post-loss protocol, add to log |
| Pattern emerging | Document it, create drill/fix |
| Preparing for known rival | Review their profile, past matches |
| Plateau in progress | Analyze recent losses for new patterns |
| Won against usual winner | Document what changed, replicate |
Load Reference
| Need | File |
|---|---|
| Domain-specific strategies | domains.md |
| Deep loss analysis framework | analysis.md |
| Progress tracking templates | tracking.md |
| Feedback loop mechanics | feedback.md |
Usage Guidance
This is an instruction-only improvement framework and appears coherent and low-risk. Before installing or enabling: (1) acknowledge the skill recommends creating ~/competing/ and markdown logs — avoid putting sensitive data (passwords, private keys, or confidential competitor data) into those files; (2) confirm your agent/runtime has permission to write to your workspace if you want the files created; (3) note there is no network activity or external installs expected, so risks are limited to local file creation and any data you choose to record. If you want stricter control, keep logs in a private location or avoid storing sensitive details.
Capability Analysis
Type: OpenClaw Skill
Name: competing
Version: 1.0.0
The skill bundle is benign. Its purpose is to help users track and improve competitive performance, and all instructions and content align with this goal. The only file system interaction instructed is the creation of a user-local tracking folder (`~/competing/`) and associated markdown files, which is a legitimate and expected function for such a skill. There is no evidence of data exfiltration, malicious execution, persistence mechanisms, or prompt injection attempts designed to subvert the agent for harmful purposes.
Capability Assessment
Purpose & Capability
Name/description (improve by analyzing losses, studying winners, tracking rivals) matches the contents: analysis templates, tracking formats, domain guidance and rivals intelligence. No unrelated credentials, binaries, or external services are requested.
Instruction Scope
Runtime instructions are limited to analysis prompts, templates, and a recommendation to create a ~/competing/ workspace and markdown files. There are no instructions to read system secrets, call external endpoints, or access unrelated system paths.
Install Mechanism
No install spec and no code files — instruction-only. This minimizes on-disk execution risk; nothing is downloaded or installed.
Credentials
The skill declares no environment variables, credentials, or config paths. The guidance to store logs and rival profiles locally is proportional to the claimed tracking purpose.
Persistence & Privilege
always:false and normal model invocation behavior. The skill does not request persistent system privileges or modifications to other skills; suggested local files are self-contained in the user's workspace.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install competing - After installation, invoke the skill by name or use
/competing - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release
Metadata
Frequently Asked Questions
What is Competing?
Improve systematically by analyzing losses, studying winners, and tracking progress against rivals in any competitive domain. It is an AI Agent Skill for Claude Code / OpenClaw, with 598 downloads so far.
How do I install Competing?
Run "/install competing" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Competing free?
Yes, Competing is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Competing support?
Competing is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Competing?
It is built and maintained by Iván (@ivangdavila); the current version is v1.0.0.
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