List platforms

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

The annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds substantial behavioral context beyond that: it explains platform states ('off', 'connect_off'), their effects on post creation and connections, the fact that disabled platforms remain listed, and the variant gating mechanism (e.g., LinkedIn organization pages). It also mentions error codes and conditions. No contradiction with annotations; this is high-value transparency.

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 longer than typical but earns its length because it covers nuanced platform states, error behaviors, and variant handling. It front-loads the core purpose and usage, then elaborates on edge cases. While a bit dense, every sentence adds essential information for correct tool selection and use. It is well-organized and not padded.

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?

Given the tool's moderate complexity and the absence of an output schema, the description adequately covers the main contextual aspects: what states exist, what errors to expect, and what fields are present (enabled, reason, variants). It does not provide a full return structure, but it hints at the keys. For an agent needing to decide when to call and interpret results, this is sufficient, though a sample response could improve 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?

The tool has zero parameters, and the schema coverage is 100% (since there are no properties to document). According to the rubric, a baseline of 4 applies for 0 params. The description correctly does not attempt to describe parameters because none exist; it focuses on behavior and return context. No additional parameter semantics are needed.

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 clearly states the tool's purpose: 'List every social platform BulkPublish supports and whether it is currently available.' It uses a specific verb ('list') and resource ('social platform'), and explicitly mentions the key data ('availability'). This distinguishes it from sibling tools like list_channels and list_rss_feeds, which deal with different resource types. No ambiguity.

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 gives explicit when-to-use guidance: 'Check this before telling a user they can connect a platform or scheduling a post to one' and 'Use this when the user asks which platforms are supported or available, or a connect/publish attempt failed with PLATFORM_DISABLED.' It also explains consequences of states (off, connect_off) and error conditions, leaving no doubt about the appropriate scenarios.

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