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

Annotations already mark this as read-only and non-destructive, so the description does not need to repeat that. It adds genuinely useful behavioral context: 132 of 196 sources have placeholder citation titles pending backfill, and the agent is told to check `citationPlaceholder` before trusting `title`/`venue`. It also discloses the inclusion criterion that every source has at least one derived finding.

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 description is front-loaded with the core action and object, then gives the important data-quality caveat and optional filters. Two sentences carry a substantial amount of relevant information with no filler. Every clause 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?

For a read-only list tool with a full output schema present, the description is complete: it defines the source set, the inclusion rule, the optional filters, and the critical placeholder-data warning. An agent has everything needed to decide whether to call this tool and how to use its filters.

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 schema already documents both parameters. The description still adds value by clarifying that `query` is a case-insensitive substring over authors/title/venue and that `camsDimension` restricts to sources with at least one finding on that dimension. This reinforces and slightly extends the schema descriptions without contradicting them.

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 has a specific verb and resource: 'List the 196 source records behind Performix's Performance Science Library.' It clearly defines what each source is (a book, paper, or corpus item with at least one derived finding) and the CAMS dimensions touched. This distinguishes it from sibling list tools like list_books or list_guides by focusing on evidence sources specifically.

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 clearly explains the optional filters and the data context ('Same source list rendered at performix.app/learn/evidence'), so an agent can infer when listing makes sense. However, it never explicitly says when to prefer this over sibling tools like get_evidence_source or list_books, nor does it give an exclusion condition. Usage guidance is implied rather than stated.

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