Objective Trust

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

Far beyond the annotations, it discloses the key trait that this tool does not execute anything ('execute=caller: you call mcp_url and pay that server'), that Down or stale probes are uncallable, that sponsorship does not affect scores, that missing history yields outcome_samples=0 with reason INSUFFICIENT_HISTORY, and that paid REST access costs $0.005 via x402. Annotations (readOnlyHint=true, openWorldHint=false) are consistent with a caller-supplied-candidate ranking operation.

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 lead sentence carries the core purpose and return shape, and every following sentence adds a discrete operational fact. The telegraphic fragments ('execute=caller: you call mcp_url and pay that server') and the unexplained x402 clause cost some readability, keeping it below a clean 5.

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 no output schema, the description compensates by naming the return fields (pick, fallbacks, reasons) and the sentinel values (INSUFFICIENT_HISTORY, outcome_samples=0), and it covers cost, probe staleness, and sponsorship neutrality. An agent has everything needed to invoke it and interpret the result.

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 parameters are already documented, but the description still adds real semantics: policy_id comes from set_objective and omitting it falls back to the default safety policy. It adds nothing further for task or candidates beyond the schema text.

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 first sentence names a specific verb (rank), a bounded resource set (1-8 MCP candidates), and the temporal scope (before paying any of them), plus what comes back (pick, fallbacks, reasons). It is clearly distinguishable from record_outcome and set_objective, and it explicitly hands off to set_objective for policy_id.

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 states the decision point for calling it ('before paying any of them') and the handoff from set_objective for policy_id, which is real routing guidance. It stops short of naming when not to call it or what to do for a single candidate, so it is not a full when/when-not/alternative map.

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 a non-read-only, non-idempotent write, and the description adds real context beyond them: the call is free, the key must own the recommendation_id, and the data feeds this key's private history rather than a public leaderboard. It does not address what happens on duplicate submissions, which matters given idempotentHint=false.

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 short sentences, front-loaded with the cost signal ('Free.') that an agent would want before deciding to call. No redundant restatement of the 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?

With no output schema, the description still conveys sequencing, ownership scoping, cost, and downstream effect on ranking. The main omission is duplicate/retry behavior for a non-idempotent write, which the annotations alone flag but do not explain.

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% and every parameter is documented in the schema itself. The description echoes success, latency_ms, and cost_usd without adding format or validation meaning 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?

The description states a specific action (report success, latency_ms, and cost_usd after a pick) and frames it as the counterpart to ranking, which distinguishes it from rank_tools_for_task. It stops short of a single crisp verb+resource sentence, relying on 'report' and 'the pick' rather than naming the resource outright.

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?

'After you call the pick' gives an explicit trigger condition and ordering relative to the sibling rank tool. The constraint that only a recommendation_id issued to this API key is accepted adds a clear precondition, though no explicit 'when not to use' case is 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 readOnlyHint=false, the description adds real value: ambiguous input returns needs_confirmation and does not overwrite a saved policy, the source sentence is not stored (privacy), and it requires the same API key as /mcp. It still doesn't spell out what a successful write does to the previously saved policy beyond the negative case.

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?

Four short sentences, front-loaded with the cost and the core transformation, then the ambiguity and privacy caveats. 'Free.' as an opener is unusual but informative; no sentence is 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?

No output schema exists, so the description carries the return burden and does so adequately by naming the output fields and the needs_confirmation path. The exact success response shape (confirmation vs. echoed weights) remains slightly underspecified.

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% and the single parameter is documented as an owner sentence with max 500 chars. The description adds semantics the schema lacks — what the sentence is parsed into and how ambiguous text is handled — which meaningfully compensates.

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+resource framing: it turns one owner sentence into trust_weight, cost_weight, and max USD per call, which tells an agent exactly what the tool produces. It doesn't explicitly contrast with siblings rank_tools_for_task or record_outcome, but the transformation is distinct enough to be recognizable.

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?

'Free.' and the ambiguity/needs_confirmation behavior imply this is a low-risk setup step, but the description never states when to call it versus the sibling tools or what prerequisites exist beyond the API key. Usage is inferable rather than stated.

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