Endpoint Tenure Verdict

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

With no annotations, the description carries full behavioral burden and does not meet it: it never says whether this is a pure read-only computation or a write that persists a 'receipt', whether a disagreement is detected and reported or merely recorded, or whether identical verdicts are an error. The word 'receipt' hints at a persisted artifact but nothing confirms it.

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 front-loaded sentence with no filler, and the parenthetical is well placed. It is efficient, though the terseness is part of why behavioral and parameter gaps remain.

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 two-required-param domain tool with no annotations, no output schema, and 0% schema coverage, the description leaves too much unknown: what a receipt contains, whether it is stored, and what tenure values are acceptable. The single sentence is not sufficient to call the tool confidently.

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 0%, so the description must supply all parameter meaning. It does partially: 'probe' is documented as a verdict taking LIVE/DEAD even though the schema declares no enum, which is genuinely useful. 'tenure' is only described circularly as a 'tenure verdict', leaving its expected values and format unknown.

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 verb 'join' and the resource 'disagreement receipt' are specific, and the tool is distinguishable from the sibling tenure_verdict because it consumes tenure output rather than producing it. However, the domain jargon ('probe verdict', 'tenure verdict', 'disagreement receipt') is left undefined, so an agent cannot tell concretely what artifact it produces.

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?

There is no statement of when to call this versus alternatives, no prerequisite ordering (e.g., 'call tenure_verdict first to obtain the tenure argument'), and no exclusions. The only implied usage is that both verdicts must already exist, which the agent must infer from the required params.

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. It implies an assessment ('Grade', 'live witness audit') but never states whether the tool is read-only, whether the live endpoint mode makes a network call with side effects, what permissions are needed, or what 'grade' produces.

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 front-loaded sentence with the action first and the mode caveat in a parenthetical. It is dense with jargon but no sentence is wasted.

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?

Three parameters, nested objects, no annotations, and no output schema — the description does not explain the return shape (a letter grade? numeric score?), what happens on partial inputs, or the semantics of the fixture pair. For this complexity level the description is under-specified.

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 0% and the description only loosely explains the mode split: baseline/current form a 'fixture pair' and endpoint drives a 'live witness audit'. The two object parameters have no documented internal structure, and the relationship/requiredness between modes is left ambiguous (all params optional).

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 verb 'Grade' and the resource 'an endpoint domain's tenure against an approval-time baseline snapshot' are stated, so the general action is identifiable. However, the domain jargon ('tenure', 'approval-time baseline', 'fixture pair', 'live witness audit') makes it hard to know concretely what is evaluated or returned, and sibling disagreement_receipt is never referenced.

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 parenthetical implicitly tells the agent which parameters select which mode: a {baseline, current} fixture pair versus {endpoint} for a live audit. That is real mode-selection guidance, but there is no explicit when-to-use, no exclusion criteria, and no guidance on choosing this tool over disagreement_receipt.

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