freedom-mcp

generate_html_visual

Generate a small, self-contained HTML visual (comparison table, simple diagram, annotated list, mini-dashboard) as a throwaway artifact for the operator's screen — not a webpage, not persisted content. Use when a quick visual explainer communicates a decision or teaching moment better than plain chat text.

Routing: Quick throwaway visual (table/diagram/list/dashboard) for THIS conversation → use this. Not for a webpage or persisted content — it renders once, inertly, in the well.

[sensitive-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]

Input Schema

TableJSON Schema

Name	Required	Description
`title`	No	Optional short title for the artifact record. Defaults to a truncated version of the prompt.
`prompt`	Yes	What to visualize — e.g. "compare these three pricing tiers as a table" or "a simple funnel: 100 leads -> 40 qualified -> 12 closed".
`companyId`	Yes	FreedomOS company id to act within (you must be a member). Required for company-scoped tools.

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations provided, the description fully carries the transparency burden. It discloses the artifact is throwaway, not persisted, renders once and inertly in the well, and includes a sensitive-tier approval note about manager approval requirements—valuable behavioral context beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear first-sentence purpose, followed by usage rationale, routing, and an approval note. It is slightly long but every section carries useful information, and the routing section, while somewhat repetitive, adds clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity and full schema coverage, the description is mostly complete. It omits what the agent receives as output (no output schema), but for a generation tool, the purpose and behavior are sufficiently well-defined for selection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with all three parameters (title, prompt, companyId) having clear descriptions. The tool description itself adds no parameter-specific details beyond the schema, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Generate a small, self-contained HTML visual' with specific artifact types and explicitly contrasts with webpages or persisted content, clearly distinguishing it from sibling generation tools like generate_carousel or generate_video. The verb-resource pair is specific and informative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

A dedicated Routing section provides explicit when-to-use ('Quick throwaway visual for THIS conversation → use this') and when-not-to-use ('Not for a webpage or persisted content') guidance. It also gives the rationale: 'when a quick visual explainer communicates a decision or teaching moment better than plain chat text.'

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

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TDQS

A3.6/5.0

Disambiguation4/5

The tool set is heavily disambiguated by detailed routing descriptions, domain prefixes, and lifecycle verbs, so most tools have a clear intended purpose. However, at 297 tools there are still close pairs and overlapping decision surfaces (e.g., approval workflows, 'what should I work on' readers, multiple finance/ads readers) that require careful description reading to avoid misselection.

Naming Consistency4/5

Naming is predominantly consistent snake_case verb_noun with strong domain prefixes like shopify_, x_, posthog_, and list_/create_/update_ patterns. Minor inconsistencies exist, such as several collection-returning tools using get_ (get_team_members, get_icps, get_okrs) instead of list_, and some generate_ vs create_ vs draft_ verbs, but the pattern is still predictable overall.

Tool Count1/5

297 tools is an extreme outlier and far beyond a usable MCP tool surface. Even a large suite has no justification for this count in one server; the agent would struggle to select among hundreds of similarly descriptive tools, and the natural 3-15 tool range is exceeded by nearly 20x.

Completeness4/5

The individual domains represented — OKRs, CRM/leads, Shopify, content pipelines, ads, PostHog, team hiring, knowledge, finance, and session management — are covered remarkably well with full lifecycle patterns. Minor gaps exist, such as no full deal CRUD, no delete for several Google/Shopify artifacts, and some analytical surfaces being read-heavy, but most workflows can be completed without dead ends.

Resources

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