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freedom-mcp

by com.getfreedomos

save_artifact

Save an artifact (screenshot, analysis, report) to the company archive. Use after browse_url to persist visual evidence, or to save any agent-produced artifact for future reference.

[write-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
NameRequiredDescriptionDefault
titleYesShort descriptive title for the artifact
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
source_urlNoURL the artifact relates to (if applicable)
descriptionNoWhat this artifact shows or contains
storage_pathNoStorage path where the file was uploaded
artifact_typeYesType of artifact being saved
metadata_jsonNoOptional JSON-encoded metadata (scores, analysis results, etc.).

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries full burden. It adds value by noting the write-tier nature and approval requirements ('first use may require a manager's approval'). This goes beyond a simple 'save' statement, though it lacks details on overwrite behavior or return values.

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

Conciseness5/5

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

The description is compact: two main sentences and a bracketed note. Core purpose is front-loaded, with additional context provided efficiently. Every sentence adds value without redundancy.

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 no output schema, the description omits what the tool returns (e.g., artifact ID, success status). It covers purpose, usage, and parameter types well, but for a saving operation, return information would be helpful for the agent. Minor gap.

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 coverage is 100%, so all parameters already have descriptions. The description lists artifact types matching the enum but adds no new parameter semantics beyond what the schema provides. Baseline score of 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 clearly states the tool saves artifacts (screenshot, analysis, report) to a company archive, specifying the verb and resource. It distinguishes use cases (after browse_url, or saving agent-produced artifacts) and is distinct from sibling tools like browse_url or save_knowledge.

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

Usage Guidelines4/5

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

The description explicitly states when to use the tool ('Use after browse_url to persist visual evidence, or to save any agent-produced artifact for future reference'). It also includes approval dynamics hints. However, it doesn't explicitly exclude alternatives like save_knowledge or other save tools.

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