get_project_state

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

Discloses key behavioral traits: returns durable lifecycle records only, no synthesis, specific included fields, return type (dict), and error condition (LookupError). With no annotations, this is strong coverage, though side effects and auth are not mentioned.

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?

Concise yet informative: first sentence gives purpose, followed by exclusions, inclusions, return format, and error. No wasted words.

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 an output schema present, return values are adequately described. The parameter is minimal and self-explanatory. Overall, the description covers essentials for a single-parameter read tool, though parameter explanation would improve completeness.

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?

Only parameter 'project_key' has no description in schema (0% coverage) and description does not explain it. The tool relies entirely on the parameter name for meaning, which is insufficient.

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?

Clearly states verb 'Return' and resource 'raw governed state for a project'. Explicitly distinguishes from siblings by listing exclusions (no synthesis, no LLM output) and inclusions (objective, open loops, etc.), making the tool's unique role obvious.

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?

Provides clear context on what the tool returns and excludes, allowing inference of when to use it (comprehensive state) vs siblings (specific components). However, lacks explicit 'when to use' or 'when not to use' statements.

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