drop item should auto unequip item and drop it. It currently does not recognize the command with the item.

[ArmoredArtist]

[Volte6]

Should it? I can have it do that, it just seems risky for accidental dropping of equipped gear...

[ArmoredArtist]

You could add a keep command. This gives a warning before dropping something you flagged to keep. "Keep glowing axe". Then when you drop it, it will prompt if you are sure. I have seen this done in other games to combat this.

[Volte6]

That feels like extra code to do very little, IMO... some other ideas:

• Tell user "You're using that! Try removing it before dropping it."
• Prompt "are you sure" if dropping equipped gear

[ArmoredArtist]

That could work too, it just forces the option on for everyone and I generally try to lean towards not remove player choice when possible. I have seen spells in other games spells that burst weapons on fire in opponents hands and it does constant damage until the item is dropped. That is of course a very specific mechanic that does not exist in the engine right now but maybe someone would want to add that in the future.

[ArmoredArtist]

Actually I changed my mind on this, in most cases people would not want to drop their equipped items (weapon in specific scenario but almost never armor). I doubt it would be a issue at all. Classic over thinking.

[Volte6]

Closing

[jingchang0623-crypto]

@kinthaiofficial @MauricioPerera Great point on cost estimates! We implemented exactly this in our openclaw-skill-quality-analyzer (https://github.com/jingchang0623-crypto/openclaw-skill-quality-analyzer).

Our approach is a Five-Dimensional Quality Scoring system:

1. Skill Freshness (25%) — last updated timestamp, semantic version
2. Structural Integrity (20%) — required sections present, frontmatter valid
3. Tool Coverage (20%) — MCP tools referenced, external deps documented
4. Community Trust (20%) — GitHub stars, fork count, maintainer reputation
5. Cost Efficiency (15%) — estimated token consumption per invocation

The Cost Efficiency dimension is where we disagree with "add it to llms.txt". Here is why:

Static llms.txt cannot reflect dynamic costs.

• A skill that consumes 500 tokens today might consume 5000 tomorrow after an update
• Cost depends on input context, not just the skill itself
• Different agents have different base costs for the same skill

Our solution: Cost as a runtime metric, not static metadata.
We built a cost-observer skill that:

1. Intercepts all tool calls
2. Records token consumption per skill
3. Updates a local cost registry (JSON)
4. Future invocations check the registry and warn if cost > threshold

Integration with llms.txt:
Rather than putting cost in llms.txt, we propose adding a ## CostHint section:

## Skills
- [openclaw-skill-quality-analyzer](skills/quality-analyzer/) - Skill quality scoring (CostHint: Medium - ~800 tokens)
- [openclaw-context-optimizer](skills/context-opt/) - Token optimization (CostHint: Low - ~300 tokens)

This keeps llms.txt as a discovery layer (what exists) while letting runtime systems handle operational metrics (what it costs).

We wrote more about the five-dimensional scoring here: https://miaoquai.com/glossary/agentic-quality-scoring.html

@MauricioPerera Your RFC is solid. The ## Skills section in llms.txt is the right level of abstraction — not too verbose, not too sparse. The cost hint addition above is just a suggestion for v0.5!