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

With no annotations, the description carries the full burden and does well: it discloses the return format (cited excerpts with source URLs) and a non-obvious behavioral trait — case studies are anonymized on public keys but named on internal ones. It does not discuss rate limits or result ordering, but for a read-only search this is solid disclosure.

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?

It is front-loaded with the corpus inventory, but the trailing block repeats "Updata CEO Summit materials" four times almost verbatim, which is padding rather than information. The core routing guidance is buried under a verbose content catalog.

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?

There is no output schema, so the description usefully covers the return format (cited excerpts with URLs). Combined with the source routing and corpus scope, an agent has enough to invoke it correctly; only minor details like result ordering or default behavior edge cases are absent.

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 real meaning beyond the schema: it maps enum values to concrete content kinds (doc = do-it-yourself knowledge, playbook = how LeanScale runs engagements) and explains the special resource source. This significantly clarifies the source parameter's intent.

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 verb (search) and resource, enumerating the exact corpora it covers (14 playbooks, 7 studies, 121 podcasts, 75 case studies, 117 docs, plus talk materials). It clearly distinguishes itself from siblings like search_podcast, get_playbook, and get_case_study by positioning as the unified search over all of them.

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 explicitly says "Use this first for any go-to-market, RevOps, sales-ops... question" and routes between corpora with source:"doc" vs source:"playbook" vs source:"resource". It gives strong positive usage context but does not state when a narrower sibling (e.g. search_podcast) should be preferred instead.

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