Mifori CertAgent Trust Oracle

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, and the description adds substantial extra context beyond them: no authentication required, no rate limits, no cursor pagination, single-page snapshot semantics, and the tier labels returned (AAA, AA, B). This is well above the bar set by the annotations.

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?

Three dense sentences, front-loaded with the resource and ranking rules before the routing/alternatives guidance. Every clause carries information, though the middle sentence packs multiple concerns (limit values, default, tier names) tightly enough to be slightly heavy.

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?

With an output schema present, return-value detail is unnecessary, and the description still covers access model (free/unauthenticated), throttling (no rate limits), pagination behavior, ordering, and sibling routing. Nothing an agent needs to call this correctly is missing.

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 baseline is 3, but the description adds genuine meaning beyond the schema: it explains the intent behind limit=1 (best-agent selection for task routing) versus the upper bound (full tier comparison). That interpretive layer is a real addition.

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?

Opens with a specific verb and resource ('Queries a free, unauthenticated single-page snapshot of audited AI agents') and names the exact ranking keys (Synthetic IQ descending, latency ascending). It is immediately distinguishable from verify_agent_reputation and submit_agent_feedback, which are named and characterized.

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?

Gives explicit conditional guidance: limit=1 for immediate task routing, up to limit=100 for reliability-tier comparison. It also states when to use the two siblings instead ('run a fresh live audit on a specific target_bot_url' / 'report telemetry for an eval_id'), leaving nothing to inference.

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 cover the safety profile (readOnlyHint=false, idempotentHint=true, destructiveHint=false, openWorldHint=false), and the description adds substantial context beyond them: sub-100ms latency, no auth or payment required, the immediate 1-free-audit-credit side effect (reward_status='1_FREE_AUDIT_CREDIT_GRANTED'), and that blank required fields fail schema validation.

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?

Front-loads the core purpose and destructive/safety-free behavior in the first clause, then adds parameter guidance and sibling routing. It is dense and contains long run-on sentences with parenthetical examples, but every sentence carries actionable content.

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 3-parameter mutation with nested object support and an existing output schema, the description supplies everything needed: source of eval_id, expected reported_issue content, optional metric overrides, the free-credit side effect, and routing to alternatives. Return values are covered by the output schema, so their omission is appropriate.

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 baseline is 3; the description earns above baseline by adding provenance for eval_id (must reference a prior verify_agent_reputation or get_agent_leaderboard result) and a worked example for suggested_metric. It does not add much syntactic detail beyond the schema, which already documents all three parameters.

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: 'Persists machine-to-machine telemetry or score disputes for an existing audit certificate (eval_id).' It clearly differentiates from siblings by naming verify_agent_reputation as the live-audit tool and get_agent_leaderboard as the browse tool.

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?

Explicitly states when to use it ('Use after an audit to contest a score or report runtime drift') and names both alternatives with their own triggering conditions ('use verify_agent_reputation to run a new live audit, or get_agent_leaderboard to browse ranked agents'). No inference required.

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 declare readOnlyHint=false, openWorldHint=true, non-idempotent and non-destructive, but the description goes beyond them: it discloses the outbound network call, the sub-500ms latency budget, the $0.005 USDC cost with accepted payment forms, the free side-effect-free invoice path, and public-ledger persistence. That is real behavioral context an agent needs before invoking a paid, state-mutating audit.

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?

Information is front-loaded: purpose and measured outputs first, then the payment flow, then tool-selection guidance. It is dense and the second sentence is long, but every clause carries distinct information, so nothing reads as 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?

An output schema exists, so return values need not be re-explained. Given the tool's complexity, the description covers prerequisites (reachable JSON POST endpoint), cost and auth mechanics, ledger side effects, and sibling alternatives — everything needed to call it 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?

Schema description coverage is 100%, so both the payment_proof workflow ('omit on initial call to receive the free HTTP 402 payment invoice') and the POST-probe requirement for target_bot_url are already documented in the schema; the description largely restates them. The optional agent_id parameter is not mentioned at all, so the description adds little beyond structured data. 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 and resource ('Executes a live <500ms outbound HTTP audit against target_bot_url') plus the concrete outputs it measures (Synthetic IQ, latency, schema compliance, hallucination risk) and the side effect of persisting a signed certificate. It also names the two siblings it is not, so an agent can distinguish it without opening other schemas.

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?

Explicitly says when to use it ('before delegating tasks to a specific endpoint') and names alternatives with their selecting conditions: get_agent_leaderboard for free read-only ranking and submit_agent_feedback to dispute an eval_id. It additionally documents the two-step invocation flow (free 402 invoice, then paid probe), leaving nothing to inference.

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