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

With no annotations, the description carries the full burden and handles it well: it discloses that output is sourced rather than hallucinated, that the tool is unofficial, that it explicitly says 'I don't know' and redirects to Discord/email, and that it must never invent 2027 ticket prices. These are highly relevant honesty and fallback behaviors for an AI Q&A tool.

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 three compact sentences, each earning its place: what it does, how it handles unknown cases, and the specific prohibition on inventing ticket prices. It is front-loaded with the core purpose and contains no filler.

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 single-parameter, no-output-schema tool, the description covers the core behavior, fallback behavior, and honesty constraints well. It lacks explicit return-format details and clear routing against sibling tools, but the provided behavior is sufficient for an agent to call it correctly in most cases.

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 schema already describes the single 'question' parameter at 100% coverage, so the baseline is 3. The description adds the useful nuance that the question should be natural-language and VC6-related, but it does not provide examples or format guidance beyond the schema.

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 states that ask_vc6 turns a natural-language VC6 question into a sourced briefing from public vibe.camp pages. This distinguishes it well from search-style siblings in practice, though it does not explicitly name an alternative tool or contrast itself with search_vc6.

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?

The phrase 'natural-language VC6 question' implies this is for open-ended questions rather than structured search, but the description never explicitly says 'use this instead of search_vc6' or provides exclusion criteria. Usage context is implied rather than stated.

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

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

With no annotations, the description carries the burden. It discloses that the tool returns sourced markdown or facts and is a load, but it does not mention behavior for missing/unknown topics, authentication, or reading vs mutation beyond the verb 'load'.

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?

One compact sentence front-loads the action ('Load one VC6 topic') and includes concrete examples with no filler. Every phrase earns its place.

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?

The tool is simple with a single well-documented parameter. Without an output schema, the description compensates by stating the return type ('sourced markdown or facts'). It could add not-found behavior, but the essentials are covered.

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?

Schema coverage is 100%, so the description need not re-document the 'topic' parameter. It adds useful example topic names, but not much deeper semantic meaning, so baseline 3 is appropriate.

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?

States a specific operation ('Load one VC6 topic') with clear retrieval keys (id or name) and output ('sourced markdown or facts'). The verb and 'one' distinguish it from list/search/ask siblings.

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?

Implies use when you already have a topic id or name, and the schema points to list_topics, but the description never names alternatives or says when to use search_vc6/ask_vc6 instead. Guidance is only implicit.

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

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

With no annotations, the description carries the behavioral burden, and it does disclose the key behavior: it returns a catalog of bundled topics, each with a one-line summary and source citation. It does not detail response shape or ordering, but for a read-only, parameterless list operation this is sufficient and not misleading.

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 a single front-loaded sentence that communicates scope, content, and output characteristics without filler. Every element contributes value.

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 simple parameterless list tool with no output schema, the description covers the essential facts: what is listed, what each entry contains, and that it is a fixed bundled set. It could further clarify how it relates to get_topic or search_vc6, but that is a nice-to-have rather than a gap for invocation.

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 tool has zero parameters and the schema is an empty object, so there is nothing for the description to explain. This matches the baseline for parameterless tools; no parameter semantics are needed.

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 identifies the resource ('bundled VC6 knowledge topics') and the content of the result ('one-line summaries and source citation'), and the name list_topics supplies the verb. It is distinguishable from siblings such as search_vc6 and get_topic because it addresses a fixed catalog rather than retrieval or search, though the description itself does not explicitly say 'lists' or 'returns'.

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?

The word 'catalog' implies use when the agent wants an overview of available VC6 topics, but the description gives no explicit when-to-use/when-not-to-use guidance and never names alternatives such as search_vc6 or get_topic. Usage must be inferred from the resource type rather than stated.

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

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

Since no annotations are provided, the description carries the full burden. It discloses the return format (ranked sourced snippets and source URLs), scopes the knowledge base to facts.json + topic markdown, and adds a notable behavioral guarantee: "Does not invent ticket prices." It doesn't mention side effects or rate limits, but this is adequate for a read-only search tool.

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 two sentences with minimal filler. It front-loads the core action and purpose, then concisely lists the return type and a key limitation. Every clause contributes meaningful information.

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 simple two-parameter search tool, the description covers purpose, scope, output shape, and a behavioral guarantee. It lacks explicit routing among sibling tools and does not detail the output structure beyond snippets and URLs, but given the low complexity and the absence of an output schema, it is nearly complete.

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?

Schema description coverage is 100% (both query and limit are described in the input schema), so the baseline is 3. The description adds no parameter-specific details beyond the "keyword search" framing; it doesn't need to, but it also doesn't elevate the score.

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 states a specific verb and resource: "Keyword search over bundled VC6 / sechscamp knowledge (facts.json + topic markdown)", and clearly defines the output as "ranked sourced snippets and source URLs." While it does not explicitly name sibling tools, the search action and the "does not invent ticket prices" caveat imply differentiation from the Q&A-style ask_vc6.

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?

The description implies this is for keyword-style factual lookup and includes a limitation, but it never explicitly states when to prefer search_vc6 over get_topic, list_topics, or ask_vc6. There is no when-not-to-use guidance, so an agent must infer the intended use case from the action and output description.

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