Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses that the tool is read-only, free, returns proof_feed, and that the output is signed, chain-anchored, and checkable. This is strong, though it doesn't detail the format of the documentation output itself.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, stating core identity and purpose first. The standalone 'FREE.' fragment is slightly promotional but not harmful; the rest is dense and well-ordered.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-input tool with no output schema, the description sufficiently explains what it returns (llms.txt docs plus proof_feed) and why to call it. Minor gaps like output format or size are not critical for a documentation endpoint.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters, so there is nothing for the description to explain. Baseline 4 applies, and the description makes no misleading parameter claims.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as a documentation surface for the technocore.chat server (llms.txt) and states that it also returns proof_feed. It distinguishes itself from sibling tools like technocore_note and technocore_rooms by being the informational/docs tool, though it does not explicitly name any sibling it is not.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides an explicit 'Use this when' clause with concrete triggers: learning the technocore API or the Flop Network agent ecosystem. It lacks explicit 'when not to use' guidance or named alternatives, but the covered use cases are clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.