Sigao Li — personal MCP server

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

With no annotations provided, the description carries the behavioral transparency burden. It discloses that an unknown slug returns a list of valid slugs, which is a valuable behavioral detail. The read-only nature is implied by 'Full text' and 'get,' but no explicit authorization or side-effect clarification is given.

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 two sentences long, front-loads the core purpose, and avoids redundancy with the schema. Every clause adds useful information, making it concise and well structured.

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 retrieval tool with no output schema, the description covers the return content, the identifier (slug), the language option (via schema), and the list-of-slugs fallback. This is sufficient for an agent to effectively select and invoke the tool.

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%, supplying baseline meaning for both 'slug' and 'lang'. The description adds extra semantics for 'slug' by explaining the unknown-slug behavior and the content structure, which goes beyond the schema's terse 'Case study slug' 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 clearly states this tool retrieves the full text of a single project case study identified by slug, and explicitly names the content sections (challenge / approach / impact). This distinguishes it from siblings like get_profile and list_experience, which cover different content types.

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 clear usage context, especially the edge-case instruction to call with an unknown slug to receive a list of valid slugs. It does not explicitly mention when to use this tool versus the sibling tools, but the purpose is distinct enough to infer appropriate use.

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

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

With no annotations, the description carries the burden of disclosing behavior. It does list the content categories (identity, career narrative, contact links, self-introduction), which is useful, but it doesn't explicitly state that this is a read-only operation or describe any response format. Since 'get' implies non-mutating, this is adequate but not rich.

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 one concise, front-loaded sentence that packs meaningful detail ('identity, career narrative, contact links, and self-introduction') without any wasted words. It is appropriately sized for the tool's simplicity.

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 read-only tool with one optional parameter and no output schema, the description gives a good sense of what will be returned. It could mention the 'lang' parameter or a typical response structure, but the listed content categories provide sufficient context for an agent to select and invoke the tool.

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 parameter 'lang' has a full description in the schema (100% coverage), so the schema already explains its meaning. The tool description adds no additional parameter semantics, so the baseline score of 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 what the tool returns: identity, career narrative, contact links, and self-introduction. It names the resource (Sigao Li's profile) and implies the 'get' operation. While it doesn't explicitly contrast with siblings like get_case_study or list_experience, the content scope is distinct enough.

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: when you need an overview of who Sigao Li is, use this tool. However, it provides no explicit guidance on when not to use it or how it differs from the sibling tools, leaving the agent to infer the appropriate context.

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

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.