validate_heading_intent

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

Annotations are absent, so the description bears the full burden. It clearly communicates an analysis/lint behavior (flag generic headings and score alignment) and that implies no destructive side effects, but it omits expected output shape, scoring scale, and any access requirements. The behavioral description is adequate but far from exhaustive.

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 entire description is one sentence, opens with the key verb, includes a concrete example, and contains zero filler. Every phrase contributes to clarifying what the tool validates and what its output factors are.

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 this is a simple one-parameter tool with no output schema, the description explains the input domain (headings) and the intended judgment (generic flag + intent score). It leaves open the exact return format and how the score is computed, but those are non-critical for a tool of this low 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 description coverage is 100%, and the tool description adds only one small semantic bit: an example ('What is X') of what qualifies as a generic heading. It does not give extra insight into the 'level' field or how text relates to scoring beyond the schema. This barely exceeds the baseline for fully covered schemas.

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 ('Flags') and names the focused resource (generic AI headings) and the scoring result (user/search intent alignment). The example 'What is X' gives concrete grounding, and the function is distinct from sibling audit tools so an agent knows it's about heading validation.

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 implies the tool is for validating heading intent through its example and verb, but it gives no explicit guidance about when to choose this over siblings like lint_design_anti_patterns or audit_eeat_entity_graph, nor does it state preconditions/limitations. Usage is inferred rather than prescribed.

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