tokscale_developer_profile

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

Annotations already declare readOnlyHint=true, so the description does not need to reiterate safety. The description adds valuable behavioral context: it returns a summary, all filesystem paths are redacted (home dir → ~), and includes headless support flag. No contradictions.

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 dense with information but remains efficient; each sentence adds value. It is front-loaded with the main purpose and includes usage guidance. Minor improvement could be more structured bullet points, but overall it is concise.

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 no parameters and an existing output schema, the description covers all essential context: it describes the data returned, how paths are redacted, and provides a usage note. It is complete for the tool's purpose.

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?

There are zero parameters, and schema description coverage is 100% (trivially). Description adds meaning beyond schema by elaborating on what the returned profile includes (model mix, token pillars, etc.), which is useful context.

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 provides a per-developer usage profile across all 20+ AI tools detected by tokscale, listing specific data points like model mix, token pillars, and summary fields. It distinguishes itself from sibling tool tokscale_cost_analysis by explicitly stating it is not for cost-only analysis.

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 says when to use this tool ('to understand your full AI tool footprint') and when not to ('Do NOT use this for cost-only analysis') while directing to the appropriate alternative (tokscale_cost_analysis). This provides clear usage guidance.

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