Read-only access to Fmind's portfolio, articles, and sites.
Scored across 9 tools
Each tool targets a distinct resource or action: profile, services, certifications, experience, projects, publications, articles (retrieval and search), and a hosting cost calculator. There is no overlap; even related tools like list_publications and search_articles have clearly separated purposes (listing vs. relevant search).
All tool names follow a consistent verb_noun pattern with lower_snake_case: get_ for single items, list_ for enumerations, search_ for queries, and compare_ for the calculator. This is a uniform and predictable convention.
Nine tools is well-scoped for a portfolio server, covering personal info, services, credentials, work history, projects, publications, articles, and a specialized calculator. Each tool serves a clear purpose without unnecessary bloat or thinness.
The tool surface comprehensively covers the portfolio domain: profile, services, certifications, experience, projects, publications, and articles (with both listing and search). The hosting calculator adds a distinct capability, and there are no obvious dead ends or missing operations for the stated purpose.
Compare one GKE hosting scenario with managed API baselines using the website calculator. Call with parameters={} for defaults and supported model, node, billing, and quantization choices. Then override URL parameters as strings, e.g. requests=1000, throughput=100, tokens=500. Returns assumptions, USD costs, constraints, dated sources, and a shareable URL. Invalid inputs fail; no resources are provisioned. See /agents#calculator.
| Name | Required | Description | Default |
|---|---|---|---|
| parameters | Yes | Calculator URL parameters as strings; use an empty object for defaults and available choices. |
| Name | Required | Description |
|---|---|---|
| apis | Yes | |
| tasks | Yes | |
| units | Yes | |
| inputs | Yes | |
| models | Yes | |
| latency | Yes | |
| presets | Yes | |
| sources | Yes | |
| estimate | Yes | |
| node_pools | Yes | |
| parameters | Yes | |
| validation | Yes | |
| limitations | Yes | |
| scenario_url | Yes | |
| calculated_on | Yes | |
| quantizations | Yes | |
| snapshot_date | Yes | |
| comparison_ready | Yes | |
| model_comparisons | Yes | |
| pilot_configuration | Yes | |
| precision_comparisons | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds that 'no resources are provisioned' and that invalid inputs fail, reinforcing non-destructive behavior. It also lists return payload types, adding useful context beyond annotations.
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 a compact paragraph with every sentence adding distinct information: purpose, invocation pattern, override examples, return contents, and safety note. It is slightly longer than strictly necessary but remains efficient and front-loaded.
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?
With an output schema present, the description need not detail return formats, yet it still names the main output categories. It covers defaults, overrides, error behavior, and non-destructive nature. The pointer to '/agents#calculator' provides an escape hatch for further detail, making this adequate for a low-complexity single-parameter 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 schema already documents the 'parameters' object as URL parameter strings, but the description enriches this by explaining that empty object gives defaults/choices and providing concrete key examples (requests, throughput, tokens). This adds practical usage meaning beyond the raw schema.
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 names the specific action 'Compare one GKE hosting scenario with managed API baselines' and the resource 'LLM hosting costs'. It clearly distinguishes this calculation tool from the sibling content/readiness tools by mentioning the website calculator and return of cost 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?
The description gives concrete calling instructions: start with parameters={} for defaults, then override URL parameters with examples. It explains when to use the tool but does not explicitly mention when not to use it or alternatives, though the sibling list makes this obvious; a brief exclusion would push this to a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read a public article's complete Markdown, dates, canonical URL, and hosted section links. Use a slug from search_articles; unknown and draft articles are unavailable.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
| Name | Required | Description |
|---|---|---|
| article | Yes | |
| markdown | Yes | |
| sections | Yes | |
| canonical_url | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=true, so the read-only nature is already known. The description adds behavioral context by specifying what content is returned and what is not available (unknown/draft articles). No contradiction, and the added detail goes beyond the annotation.
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?
Two sentences, with the core action and content front-loaded, followed by a single usage note. No wasted words; every sentence earns its place.
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 single-parameter read tool with an output schema present, the description covers what is returned, what is not available, and how to obtain the required parameter. Nothing an agent needs to call it correctly is missing.
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 description must compensate. It explains that the slug should come from search_articles, which gives its origin, but does not define what a slug is or its format beyond the schema pattern. This is helpful but incomplete.
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?
States a specific verb ('Read') and resource ('public article') and lists the exact content returned (complete Markdown, dates, canonical URL, hosted section links). It also implicitly differentiates from sibling search_articles by instructing to get the slug from there, so an agent can tell them apart.
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?
Explicitly tells the agent to obtain a slug from search_articles, establishing the prerequisite and alternative tool. Also states that unknown and draft articles are unavailable, giving clear exclusions for when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return the core profile: identity, headline, job title, contact, socials, biography, and areas of expertise.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| metadata | Yes | |
| biography | Yes | |
| expertise | Yes | |
| leadership | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation readOnlyHint=true already signals that this operation is safe and read-only, so the description does not need to repeat that. The description adds value by enumerating the returned fields, which helps the agent understand the return envelope, though no further behavioral details (e.g., authentication, error conditions) are provided.
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 a single, front-loaded sentence that immediately states the action and resource before enumerating the fields. It is concise and contains no filler, earning high marks for structure.
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 zero-parameter, read-only tool with an output schema, the description is functionally sufficient: it tells the agent what resource is returned and which fields to expect. It does not discuss edge cases or alternatives, but those are not necessary given the simplicity and the presence of an output schema.
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 tool has zero parameters, and the input schema is an empty object, so there are no parameter semantics to explain. The description therefore has no additional burden here; the baseline of 4 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 uses a specific verb ('Return') and clearly identifies the resource ('core profile') with an enumerated list of its fields (identity, headline, job title, contact, socials, biography, areas of expertise). This makes the tool's purpose obvious and distinguishes it from sibling tools like get_article or get_services, though it does not explicitly name them.
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 is provided about when to call this tool versus sibling tools (e.g., get_article, list_experience). The description only states what the tool returns, leaving the agent to infer the appropriate context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List the professional services on offer (AI architecture advisory and mentoring) with availability and how to book.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| services | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint=true, so the agent knows this is a safe read operation. The description adds meaningful behavioral scope by stating the response covers availability and how to book, without claiming any booking side effect. No contradiction exists.
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 tightly packed sentence front-loads the action and object ('List the professional services on offer') and follows with useful qualifiers. Every word earns its place; no filler or repetition of schema fields.
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 parameterless, read-only list tool with an existing output schema, the description covers all necessary context: what is listed, the domain of the services, and the availability/booking details. Nothing needed for correct invocation is missing.
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 input schema has zero parameters, so the baseline for this dimension is 4. The description still helps by explaining what the returned list contains (offerings, availability, booking instructions), which is the only semantic content an agent could need.
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?
States a specific verb ('List') and resource ('professional services'), and goes beyond a label by naming the exact offerings (AI architecture advisory and mentoring) plus the availability/booking details. This distinguishes it clearly from sibling tools that cover profile, certifications, experience, projects, publications, and articles.
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 makes the tool's scope obvious—services, not profile credentials or publications—so an agent can select it without overlap. It does not explicitly name alternatives or exclusion conditions, but the sibling set is distinct enough that no stronger routing guidance is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List professional certifications, badges, and course specializations with their issuers.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| certifications | Yes | |
| specializations | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the read-only nature is covered. The description adds the scope of what is listed (certifications, badges, specializations, issuers) but does not disclose details like ordering, pagination, or whether the list is exhaustive. No contradiction with annotations exists.
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 a single, front-loaded sentence with no filler. Every word contributes meaning, naming the action, the resource type, and an important attribute (issuers).
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 parameterless, read-only list tool with an output schema, the description is fully sufficient. An agent can select and invoke this tool correctly without needing additional behavioral or parameter details.
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 tool has zero parameters and the schema coverage is 100%, so there is no parameter documentation burden for the description to carry. The baseline of 4 for no-parameter tools is appropriate.
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 uses a specific verb ('List') and a clear resource ('professional certifications, badges, and course specializations') with relevant detail about issuers. It is clearly distinguishable from sibling list tools like list_experience and list_projects because it names a distinct credential-focused resource.
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 when to use the tool: whenever an agent needs professional certifications or credentials. However, it does not explicitly state when not to use it or how it compares to alternatives such as get_profile or list_publications, leaving some routing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List professional work experience: companies, roles, descriptions, and skill tags.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| experience | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the read-only nature is known. The description adds the specific content returned (companies, roles, etc.), which is useful context beyond the annotation. No contradictions or missing side effects are apparent for this simple list operation.
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?
A single sentence that states the action and the content categories without any filler. The core purpose is front-loaded, making it highly efficient for an agent to parse.
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?
The tool has no parameters, an output schema is present (so return structure is covered), and the description sufficiently describes what is listed. Nothing an agent needs to invoke it correctly is missing.
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 coverage is trivially 100%. Per the baseline for zero parameters, a score of 4 is appropriate; the description adds no parameter details because none exist.
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 uses a specific verb ('List') and resource ('professional work experience') and enumerates the returned fields (companies, roles, descriptions, skill tags). It clearly distinguishes from sibling tools like list_certifications or list_projects by naming the exact domain.
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 work experience is needed, but it does not explicitly state when to prefer this over alternatives or mention any exclusions. The context of sibling tools makes it obvious, but no direct guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List open-source projects and educational YouTube series.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| open_source | Yes | |
| youtube_series | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds no behavioral context such as ordering, filtering, deduplication, or scope limitations; 'open-source projects and educational YouTube series' defines content, not behavior. There is no contradiction, but the description also contributes no extra behavioral transparency.
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 a single clear sentence front-loaded with the verb 'List.' It contains no filler, no repetition of the tool name, and no extraneous details. Every word earns its place.
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?
This is a simple, zero-parameter list tool with an existing output schema and read-only annotations. The description fully captures the semantic domain, and nothing needed to invoke the tool correctly is missing. Sibling tools are distinct enough by name for an agent to differentiate.
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 tool has zero parameters, so the schema is trivially complete at 100% coverage. The rubric sets a baseline of 4 for zero-parameter tools, and the description correctly has nothing to add about parameters.
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 states a specific verb 'List' plus the exact content scope: 'open-source projects and educational YouTube series.' It distinguishes itself from sibling tools like list_certifications and list_publications by naming the resource precisely. The title adds nothing beyond the description, which is appropriate.
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?
There is no guidance about when to use this tool versus its siblings such as list_publications or search_articles. The description does not express any exclusion condition or contextual trigger. Tool selection is left entirely to inference from the name and domain context, so this is a missing-guidance case rather than an implied one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List academic and written publications: the PhD thesis, peer-reviewed papers, and hosted articles.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| papers | Yes | |
| thesis | Yes | |
| articles | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already signals a safe read operation. The description adds content-specific detail about what categories of publications are included, which goes beyond the annotation. It does not discuss sorting or pagination, but the output schema likely covers return details.
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?
A single, well-structured sentence that immediately identifies the resource and enumerates its scope. There is no wasted text or padding.
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?
With no parameters, a clear resource scope, an output schema present, and read-only annotations, the description is complete for an agent to invoke the tool correctly. Nothing essential is missing.
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 tool takes zero parameters, so the description carries no parameter-semantics burden. The schema is empty, and the baseline for zero-parameter tools is 4.
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 uses a specific verb ('List') and resource ('publications'), and enumerates the included content types (PhD thesis, peer-reviewed papers, hosted articles). This clearly distinguishes it from sibling tools like list_projects and list_certifications.
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 intended use case is clear: list all academic and written publications of a person. No explicit exclusions or alternative tool guidance is given, but the resource scope is unambiguous against siblings such as search_articles.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the hosted articles by relevance (BM25 over titles, tags, descriptions, and full text) and return the best matches. Use it to answer what Fmind has written about a topic instead of listing every publication.
| Name | Required | Description | Default |
|---|---|---|---|
| tag | No | optionally keep only articles with this tag, case-insensitive: Agent, Coding, LLM, RAG, MLOps, Cloud, Python, Project, Demo, Guide | |
| limit | No | maximum number of results to return (default 10, maximum 50) | |
| query | Yes | words to search for across article titles, tags, descriptions, and full text |
| Name | Required | Description |
|---|---|---|
| query | Yes | |
| total | Yes | |
| articles | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds meaningful behavioral detail beyond that: it reveals the ranking mechanism (BM25) and the set of fields searched, which helps an agent understand what matches and how results are ordered. This goes beyond the annotations without contradicting them.
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?
Two sentences, zero filler. The first sentence states the mechanism and behavior; the second gives the intended use case and differentiates from listing. Everything earns its place.
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 simple 3-parameter schema, the presence of an output schema, and the read-only annotation, the description covers the core purpose, usage guidance, and matching behavior. It lacks only minor details like handling of empty queries or sorting edge cases, but those are not necessary for correct tool selection and invocation.
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%, and the schema already explains query, tag, and limit in detail, including defaults, max, and tag enum values. The description does not add new parameter-level meaning beyond restating the searchable fields, so the baseline of 3 is appropriate.
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 states a specific action ('Search'), a specific resource ('hosted articles'), and a clear scope (BM25 over titles, tags, descriptions, and full text). It also distinguishes itself from listing every publication, which maps to a sibling tool, making its purpose unmistakable.
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 gives an explicit use case ('answer what Fmind has written about a topic') and an implicit alternative ('instead of listing every publication'). It does not name the sibling tool (list_publications) directly, but the guidance is clear and actionable without being vague.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
search_articles1 field changedInput schema / properties / tagAdded value: +{
+ "anyOf": [
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "optionally keep only articles with this tag, case-insensitive: Agent, Coding, LLM, RAG, MLOps, Cloud, Python, Project, Demo, Guide",
+ "title": "Tag"
+}get_profile2 fields changedOutput schema / $defs / Metadata / properties / work_locationAdded value: +{
+ "title": "Work Location",
+ "type": "string"
+}Output schema / $defs / Metadata / requiredPrevious value: -[
- "name",
- "alternate_name",
- "site_name",
- "title",
- "job_title",
- "headline_primary",
- "headline_secondary",
- "description",
- "keywords",
- "email",
- "calendar_url",
- "site_url",
- "twitter_handle",
- "socials"
-]New value: +[
+ "name",
+ "alternate_name",
+ "site_name",
+ "title",
+ "job_title",
+ "headline_primary",
+ "headline_secondary",
+ "description",
+ "keywords",
+ "email",
+ "calendar_url",
+ "site_url",
+ "twitter_handle",
+ "socials",
+ "work_location"
+]compare_llm_hostingget_articlesearch_articles1 field changedInput schema / properties / limit / defaultPrevious value: -0New value: +10get_profileget_serviceslist_certificationslist_experiencelist_projectslist_publicationssearch_articlesRead-only Fillfolio portfolio: net worth, holdings, cash, liabilities, and activity.
Read-only access to Sigao Li's profile, CV and case studies. Bilingual (EN/ZH).
Read-only access to your net worth, wealth percentile, projections, splits and budget.
Read-only access to your own Pithflow meeting notes, transcripts, dictionary and usage.
Add one secure layer between your agents and this server.