recommend_partitioning_and_archiving

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

No annotations are provided, so the description carries the full behavioral burden and falls short. It never says whether the tool is advisory-only or emits DDL/executes anything, what the runbook output looks like, or whether validation failures change the result; 'zero-bloat partition detach/drop' is a useful flavor detail but not a disclosure of side effects or return shape.

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 layering the three capabilities with no filler, which is efficient. Slight deduction for the opaque 'PART-PK-001' rule code, which consumes space without clarifying anything to an agent.

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 6-parameter, 3-required tool with no annotations, no output schema, and zero schema description coverage, the description is too thin. It omits output shape, failure modes, and the meaning of half the inputs, so an agent cannot confidently invoke it on the first try.

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% across 6 parameters, so the description must compensate and largely does not. It hints at partitioning strategy, retention, and composite-PK validation, but never explains dialect (the one enum), table_ddl, estimated_total_rows, monthly_growth_rows, or common_query_filters, all of which an agent must guess at.

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?

Three specific verbs (design, validate, generate) mapped to specific resources (table partitioning strategies, composite PK constraints, retention runbooks) with the RANGE/LIST/HASH scope stated. This clearly distinguishes it from sibling tools like recommend_indexes_for_queries or calculate_db_capacity_and_config, though it never names those siblings explicitly.

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 use this versus the capacity, index-recommendation, or migration-planning siblings, nor any prerequisites or exclusions. The partitioning/retention topic implies the situation, but an agent must infer that this is for large tables with growth and retention needs rather than being told.

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