Agent Reputation Registry

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

No annotations are provided, so the description carries the full behavioral burden. It discloses the return shape (score 0-100 and a grade), which is genuinely useful, but says nothing about auth requirements, rate limits, or what happens for an unknown or unregistered agent_id.

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?

Two short sentences, zero waste, with the capability statement front-loaded ahead of the usage trigger. Nothing is redundant or padded.

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 read tool, the description covers what it queries, the output scale, and when to invoke it. Without an output schema the grade/score mention is helpful, though the absence of error or freshness semantics leaves a small gap.

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 a single required agent_id parameter already documented in the schema. The description adds no syntax, format, or validation detail beyond what the schema provides, so the baseline 3 applies.

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 verb (query) and resource (AI agent reputation score and grade), and the 0-100 range makes the returned artifact concrete. It does not explicitly contrast with siblings like get_profile or endorse_agent, but the reputation/grade framing is distinct enough for an agent to select it.

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?

"Use before trusting or hiring another agent" gives a clear decision context for when this tool applies. There is no explicit when-not guidance or named alternative (e.g., get_profile for general data), so it falls short of a 5.

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 full behavioral burden. It usefully discloses the outcome (target's reputation score increases), but says nothing about reversibility, whether endorsements are one-per-agent, rate limits, or what happens to the endorser's own reputation.

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?

Two short sentences, front-loaded with the action and its effect, with the usage constraint second. 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 3-parameter mutation with no output schema and no annotations, the description covers purpose and effect but omits return/error behavior and mutation constraints. Adequate to invoke, but not fully informative.

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%, so all three parameters (from_agent_id, to_agent_id, comment) are documented in the schema. The description adds no parameter-level detail beyond that, so the baseline of 3 applies.

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 verb (endorse) and resource (another agent) plus the effect (increases their reputation score). It is clearly distinct from siblings like check_reputation and get_profile, though it doesn't explicitly name them as alternatives.

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?

"Only endorse agents you have had good interactions with" gives explicit context for when to use it, which is more than implied usage. It lacks when-not conditions or named alternatives, but for a single-purpose tool no obvious alternative exists.

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?

No annotations, so the description carries the full burden; it discloses the shape of the returned data (endorsement history, recent activity), which is useful given there is no output schema. It says nothing about permissions, whether the lookup is read-only, behavior for an unknown agent_id, result limits, or freshness, leaving meaningful behavioral gaps.

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 front-loaded sentence that names the verb, the resource, and the payload with 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 one-parameter read tool with no annotations and no output schema, describing the returned contents is the right compensation. However, the relationship to check_reputation is left unexplained, and no access or error behavior is covered, so an agent can call it but may pick the wrong sibling.

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% for the single agent_id parameter, so the schema already documents the input fully. The description adds no format, source, or identifier-namespace detail beyond what the schema provides, making this the baseline case.

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 verb (get) and resource (reputation profile) and enumerates the payload (endorsement history, recent activity). It does not explicitly distinguish itself from the sibling check_reputation, so an agent must guess whether 'full profile' vs 'check reputation' differ in scope.

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?

No when-to-use guidance and no mention of the obvious alternative check_reputation, whose name suggests a near-identical purpose. The only hint is the word 'full', which implies broader output but is not stated as a selection rule.

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 full burden, and it does disclose one useful behavioral fact: registration seeds a reputation profile at 50. It omits whether registration is idempotent, what happens on duplicate agent_id, permission/auth requirements, and whether wallet_address triggers on-chain effects.

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?

A single sentence with zero filler, front-loading the action and immediately following with the resulting state. Nothing is redundant against the name or schema.

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 4-parameter creation tool with no annotations and no output schema, the description is thin: it does not say what registration returns or how failures are surfaced. The baseline-score detail is the only substantive behavioral addition.

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%, so all four parameters are already documented in the schema. The description adds no syntax, format, or constraint detail beyond that, so the baseline of 3 applies.

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 verb and resource ('Register an AI agent') and adds the outcome ('verifiable reputation profile with a baseline score of 50'). It is distinguishable from siblings like check_reputation and get_profile, though it never explicitly contrasts itself with them.

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?

Usage is implied by the verb and the mention of a baseline score, which signals this is for newly onboarded agents. There is no explicit when-to-use/when-not guidance, no statement about what to do if the agent already exists, and no reference to the sibling tools.

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