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freedom-mcp

by com.getfreedomos

send_slack_message

Send a message to a Slack channel or direct message to a team member. Use when user asks to "message X on Slack", "send a Slack message", "DM someone on Slack", "post to #channel", etc.

[outbound-tier — EVERY call needs a manager's approval (per-send human rail): each request queues its own approval card and sends exactly once on approve. There is no standing grant for this tool.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesThe message text to send (supports Slack markdown: *bold*, _italic_, etc.)
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
thread_tsNoOptional thread timestamp to reply in a thread
channel_nameNoSlack channel name to post to (without #), e.g., "general", "engineering". Use this OR recipient_name, not both.
recipient_nameNoName of the person to DM (e.g., "Alex", "Jordan"). Will be looked up via linked accounts or Slack directory.

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations provided, the description fully discloses critical behavior: every call needs manager approval, each request queues an approval card, and exactly one message is sent on approval with no standing grant. This is essential for an agent to understand the tool's approval gating.

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 concise with only two sentences plus an approval block, all front-loaded with the most important information. Every sentence adds value and there is no 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?

The description covers purpose, usage triggers, and behavioral transparency adequately for a tool with a well-documented schema. It could mention that the message sends as the authenticated user, but overall it is highly complete.

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%, so the baseline is 3. The description does not add additional information about parameters beyond what the schema already provides, such as markdown support for message or the mutual exclusivity of channel_name and recipient_name.

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 sends a Slack message to a channel or DM. It provides specific example intents like 'message X on Slack' and 'post to #channel', which distinctly separate it from sibling tools like send_email.

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 lists user phrases that trigger the tool, providing clear context for when to use it. However, it does not explicitly mention when not to use it or name alternatives, though the examples imply the distinction.

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