intelligence-mcp

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds behavioral context by describing the output as a side-by-side comparison matrix and listing the specific axes of comparison (creator, layer, agent delegation, etc.), which goes beyond what annotations alone provide. It could detail the return structure further, but for a 0-parameter tool with a fixed protocol set, this is sufficient.

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, front-loaded with the core purpose and immediately followed by usage guidance and an alternative. Every sentence earns its place with no redundancy.

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?

Given the tool's simplicity (no params, no output schema) and the solid annotations, the description fully covers what the tool does, when to use it, and how it differs from the sibling. The inclusion of example queries and the explicit alternative makes it complete for an agent to invoke correctly.

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?

There are zero parameters, so the baseline is 4. The description correctly omits parameter details because none exist; the input schema fully covers this (vacuously). No additional 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 uses a specific verb ('Get a side-by-side comparison matrix') and precisely identifies the resource (all five agent payment protocols) and the comparison dimensions (creator, layer, agent delegation, etc.). It also distinguishes itself from the sibling tool get_protocol_info by noting it's for the full landscape rather than single-protocol details.

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 explicitly states when to use the tool, with concrete example queries ('AP2 vs ACP', 'which protocol handles budgets?', etc.), and provides a clear exclusion: use get_protocol_info for deep details on a single protocol. This leaves no ambiguity about tool selection.

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?

The annotations already declare readOnlyHint and idempotentHint, so the safety profile is clear. The description adds the output scope but does not disclose error behavior or edge cases. This is adequate but lacks extra behavioral context beyond what annotations provide.

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 composed of two concise sentences. The first states the purpose with the output fields, and the second gives usage guidelines and a sibling alternative. No filler or redundancy.

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 read-only lookup tool with one parameter and no output schema, the description explains the return contents (creator, maturity level, repo URL, layer), usage examples, and when to avoid in favor of compare_protocols. This is complete for the tool's complexity.

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%, with the protocol parameter fully described including enum and examples. The description complements this with usage examples but does not add new technical detail beyond the schema, so the 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?

The description uses the specific verb 'Get' and resource 'canonical description of an agent payment protocol', listing the fields returned (creator, maturity level, repo URL, layer). This clearly distinguishes it from sibling tools like compare_protocols.

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?

Explicit usage guidance is provided: 'Use when the user asks about a specific protocol' with concrete example queries, and the alternative 'Use compare_protocols instead' when comparing multiple protocols. This leaves no ambiguity about when to use this tool.

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?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description doesn't need to restate read-only behavior. It adds valuable context beyond annotations: the cost ($0.01 USDC), accepted payment methods, and that results are AI-classified and scored. These are useful behavioral traits not evident from annotations alone.

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 moderately long paragraph but every sentence adds value: purpose, return type, usage examples, alternatives, cost, and payment methods. It is dense but not wasteful; a slightly more structured format (e.g., bullet points) could improve scannability, but it remains efficient for the amount of 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?

Given the tool's moderate complexity (scanning multiple sources, AI classification, cost, payments) and no output schema, the description provides a complete enough picture: what it returns, when to use it, cost, and payment methods. It doesn't mention result limits or pagination, but for a scan tool with good annotations, this is adequate without being exhaustive.

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% with clear descriptions for both parameters (days and min_score), so the schema already carries the load. The tool description itself does not add parameter-specific details beyond what's in the schema, though it mentions scoring out of 20 in the min_score schema. This meets the baseline for high schema coverage.

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 uses a specific verb ('Scan') and clearly identifies resources (GitHub, Hacker News, npm) and the target domain (agent payments ecosystem). It also distinguishes itself from siblings by stating it returns AI-classified and scored opportunities with recommended actions, and explicitly names alternatives for other use cases.

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 provides direct usage guidance: 'Use when the user asks about recent activity, new developments, or opportunities in agent payments' with example queries. It also explicitly says to use get_protocol_info for static protocol details and compare_protocols for side-by-side comparison, covering both when-to-use and alternatives.

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