aimm_read_project_context

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

No annotations are provided, so the description carries full burden. It discloses return scope, cost bound, default format, and rationale. It lacks explicit statement about safety (e.g., no side effects), but the content implies read-only behavior.

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 concise, with every sentence contributing significant information. It front-loads the main purpose, followed by usage guidance and format explanation, with no redundant 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?

Given the tool's complexity (returns many project details) and lack of output schema, the description covers what is returned, when to use it, and format options. It lacks details on error handling or size limits, but the bounded cost mention mitigates some concerns.

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% with one enum parameter. The description adds value by explaining why XML is default ('cross-referential reasoning') and what markdown offers ('leaner prose digest'), going beyond the schema's basic description.

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 explicitly states 'Return everything the project records' and lists all components (header, connections, tables, joins), making the purpose unambiguous. It distinguishes from sibling tool 'aimm_init_project' by focusing on context retrieval.

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 a clear directive: 'Always call this once at the start of a session before answering data-model questions', which tells the agent exactly when to use it. It also contrasts with other tools by stating this is the 'canonical context'.

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