get_blackboard_value

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

Annotations already cover readOnly/idempotent/non-destructive/not-open-world, and the description adds real value beyond them: the blackboard-resolution fallback order, the PIE exclusion, and the key-type-to-value-type mapping. It still doesn't say what happens when the key or blackboard is missing (error vs. null).

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?

Dense but earned: scope, resolution rule, type mapping, and return shape, with the primary purpose front-loaded. The parentheticals make it slightly run-on, and the returns block is somewhat listy for a two-sentence description.

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?

With no output schema present, the explicit return shape ({actor_name, key_name, key_type, value}) is a genuine contribution. Scope and typing are covered; missing-key / no-blackboard failure behavior is the remaining gap.

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 100% for both parameters, so the schema already defines actor_name and key_name adequately and this is the baseline case. The description adds only indirect meaning (key types determine the returned value type) rather than new parameter-level detail.

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?

States a specific verb (Read) and a tightly scoped resource (one key of the running blackboard of an editor-world actor), plus the resolution rule (AIController blackboard, else one on the actor). That precision readily separates it from bulk-reading siblings such as get_blackboard_data/get_blackboard_keys and the write-side set_blackboard_value.

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 a clear operating context and an explicit exclusion: read-only, editor world only, never PIE. It does not name a sibling alternative for the 'I want everything' case, so the routing signal is strong but not complete.

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