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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so safety is covered; the description adds genuinely non-obvious behavior: optional filters combine with AND, string matching is case-insensitive and exact rather than substring, and a zero-match query returns `hint` and `valid_values` so a typo is distinguishable from a coverage gap. It also explains why `persona_primary_only` exists (broad personas like Engineering collaborate on nearly every file). Minor deduction because the stated return shape largely restates the existing output schema.

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?

Front-loaded with purpose, then usage triggers, then matching semantics, then per-parameter detail, then return shape — a logical order for an agent reading top-down. The five worked call examples are efficient illustrations, though the Args section slightly duplicates the schema property names and the return-shape sentence could be trimmed given the output 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?

For a six-parameter, all-optional filter tool with an output schema, everything an agent needs is present: which facet values are legal, how filters combine, how strings are matched, how to disambiguate the one non-obvious boolean, and what an empty result looks like. No open questions remain before calling it.

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 carries the full burden and does: each of the six parameters is defined with accepted vocabulary (phase = Inform/Optimize/Operate, maturity = Crawl/Walk/Run, sample domain strings) and match targets (capability hits both fcp_capability and fcp_capabilities_secondary; persona hits primary and collaborating). The `persona_primary_only` semantics are spelled out precisely, including the default-vs-strict contrast.

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?

Opens with a specific verb and resource ("Find which guidance serves a FinOps question") and enumerates the question space it covers (commit, size, allocate, charge back, forecast, govern). The closing contrast — "only the references that serve it, instead of scanning the full list" — separates it from list_references and get_reference without the agent needing to open those schemas.

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?

Gives concrete trigger utterances ("how should we size Savings Plans", "what does a Crawl-stage org tackle first") plus the general rule that the question maps to a FinOps Framework facet. It explicitly routes away from the sibling bulk-listing behavior by stating this returns only matching references rather than the full list.

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