list_experienceFull CV: current role, professional experience, research, education, volunteering, awards, skills, certifications.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Language of the returned content ('en' or 'zh'). | en |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden. It implies a read-only operation but does not explicitly state side effects or security considerations. It does add context by enumerating the CV sections.
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?
One concise sentence that effectively communicates the tool's scope with no wasted 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?
For a simple list operation, the description lists all content areas and is sufficient despite lacking an output schema or mention of siblings. It could be more explicit about return format, but overall it provides the essential context.
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?
The single 'lang' parameter is fully described in the schema with an enum and description. The tool description adds no additional parameter semantics, so baseline 3 applies.
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 lists a full CV with specific sections, distinguishing it from sibling tools like get_case_study and get_profile which likely return narrower data.
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?
No guidance on when to use this tool versus siblings. The description only defines the output scope; no explicit alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource: case studies, profile, and CV. No overlap in purpose or functionality.
All tools follow a verb_noun pattern (get_* and list_*), which is consistent and predictable.
Three tools is slightly minimal but appropriate for a personal server covering profile, CV, and case studies.
Core personal information and case study retrieval are covered. The only minor gap is that case study listing relies on an invalid slug call rather than a dedicated list tool.