Get project context

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

Annotations declare readOnlyHint=true and openWorldHint=false, so the description does not repeat that. It adds context about the content being 'persistent' and that 'index' is the default topic, which is useful. However, it does not disclose details like what happens if a topic is not found, or the exact format of the response (e.g., plain text vs JSON). Since annotations already cover safety, a 3 is appropriate—description adds some value but lacks behavioral depth beyond the schema.

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 two sentences: the first lists what the tool reads, the second gives a clear usage instruction. No fluff, every word earns its place. It front-loads the purpose and immediately follows with actionable guidance, making it highly scannable for an AI 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?

Given the simplicity (single optional parameter, no output schema, benign read operation), the description is nearly complete. It explains the tool's role and how to invoke it. However, it could mention what happens with a specific decision ID (like returns that decision) but that is implied. The lack of output schema means the description should hint at the format, but since the schema already covers parameters, this is still rated high.

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%, so the schema already documents each topic value. The description adds a little by mentioning 'index' as default and that 'decisions' and 'plans' are list-only, which is not in the schema. It also explains the purpose of the parameter ('What to read'). Since schema does the heavy lifting, a 3 is baseline, but the extra specification of list-only and default raises it to 4.

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 reads the project's persistent AI context and lists the specific content types (index, project description, constraints, decisions, plans, memory). It distinguishes itself from siblings like record_note and record_decision by emphasizing it is a read operation, and it differentiates from list_context by targeting specific context areas. The verb 'Read' plus the resource 'persistent AI context' is specific and actionable.

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 explicitly instructs to call with no arguments at session start to orient, which is a clear when-to-use guideline. It also implies that for listing all context, you might use list_context, but it does not explicitly exclude alternatives. However, the instruction to use at session start is a strong usage signal, and the sibling list_context likely covers the 'when not' implicitly. The guidance is clear and actionable.

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