Aedifion MCP Server

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

No annotations are provided, so the description carries the full burden. It states the tool can 'overwrite' a tag, indicating mutation behavior, but doesn't disclose other critical traits: whether it requires specific permissions, if changes are reversible, rate limits, or what happens on success/failure. The description is minimal and lacks behavioral context beyond the basic action.

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 front-loaded with the core purpose in the first sentence, followed by a structured Args section. It's efficient with minimal waste, though the Args formatting could be more integrated. Every sentence serves a purpose, but the structure is slightly fragmented between description and parameter list.

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 has 4 parameters with 0% schema coverage and an output schema (which reduces need to describe return values), the description is moderately complete. It covers the basic action and parameters but lacks behavioral details, usage context, and deeper parameter semantics. For a mutation tool with no annotations, it should do more to compensate for the missing structured data.

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 0%, so the schema provides no parameter descriptions. The description lists all four parameters with brief labels (e.g., 'Tag key', 'Tag value'), adding some semantic meaning beyond the schema's titles. However, it doesn't explain parameter relationships (e.g., how tag_id, key, and value interact) or provide examples, leaving gaps in understanding.

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 action ('Add or overwrite') and target resource ('a tag on a datapoint'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'delete_project_tag' or 'get_project_tags', though the verb 'add/overwrite' implies creation/modification versus deletion or 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing project or tag), exclusions, or comparisons to sibling tools like 'update_project' or 'delete_project_tag'. Usage context is implied but not stated.

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