trace-mcp

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

With no annotations provided, the description carries the full burden. It discloses that decisions are manually recorded, can link to code elements, and have temporal validity with potential invalidation. However, it doesn't cover critical behavioral aspects like whether this is a write operation (implied by 'record'), authentication requirements, rate limits, or what happens on success/failure. The description adds some context but leaves significant gaps for a mutation tool.

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 appropriately concise with two sentences that efficiently convey the core functionality and key characteristics. Every sentence earns its place: the first defines the purpose and scope, the second explains temporal validity. No wasted words or redundant information.

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 (7 parameters, mutation operation) and lack of both annotations and output schema, the description is moderately complete. It covers the what and why of decision recording but misses important contextual details like expected response format, error conditions, and operational constraints. For a write tool with rich parameters, more completeness would be beneficial.

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 all 7 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema descriptions. It mentions linking to code symbols/files and subprojects, which aligns with parameters like 'symbol_id' and 'service_name', but doesn't provide additional semantic context. Baseline 3 is appropriate when schema does the heavy lifting.

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's purpose: 'Manually record an architectural decision, tech choice, preference, or convention.' It specifies the verb ('record') and resource ('decision'), and distinguishes from siblings by focusing on decision recording rather than analysis or querying. However, it doesn't explicitly differentiate from 'invalidate_decision' which handles invalidation of decisions.

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 implies usage context by mentioning 'temporal validity' and linking to code symbols/files, but doesn't provide explicit guidance on when to use this tool versus alternatives like 'query_decisions' or 'get_decision_stats'. It mentions decisions can be invalidated later, which hints at a lifecycle, but lacks clear when/when-not instructions.

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