search_permit_requirements

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

No annotations are provided, so the description carries the full burden. It discloses the engine type (local, section-aware RAG), the sources covered, and a token-reduction figure, which is genuine behavioral context. It omits safety/mutation profile (implied read-only), latency, accuracy, and freshness/update behavior, leaving meaningful gaps for a zero-annotation tool.

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 Args/Returns structure is clean and front-loads the purpose, but there is waste: the 'Rule 3' tag is unexplained and the '82.9% context token reduction' claim is marketing rather than actionable for an agent. Reasonable size overall, but not every sentence earns its place.

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-value detail is largely duplicated, but the description still adds useful framing (citations, section numbers, relevance scores, excerpts). Combined with full parameter coverage, an agent has enough to invoke the tool correctly. Only the interaction with sibling tools is left unaddressed.

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 0%, so the description must compensate, and it does: all four parameters are annotated with purpose, examples, and the top_k default. It explains that jurisdiction and permit_type are filters and what each controls. Coverage is strong, though enum-like values are only loosely suggested rather than enumerated.

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 names a specific verb and resource: a section-aware RAG search over municipal building codes, amendments, and technical guidelines, with concrete domain examples (Phoenix Mechanical Code 301.5, ASHRAE 90.1, NEC 2023). This is unambiguous about what the tool does. It does not, however, contrast itself against any sibling tool, so it stops short of a 5.

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 only implied: the query examples show the intended context (structural calculations, jurisdiction/permit filters) but there is no explicit 'use this when / not when' statement and no alternatives named among the sibling tools. An agent can infer the use case but must decide on its own when this search is the right call versus, say, check_permit_readiness.

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