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freedom-mcp

by com.getfreedomos

decide_command_center_item

Approve or deny a Command Center card. This processes the decision through the full approval pipeline including trust scoring, autopilot evaluation, skill learning, and deliverable queue progression. Supports a split: close the already-decided/conforming half and spin off a separate product residual for only the novel half.

[sensitive-tier, initiates a multi-step agent process — company managers (executive/gm) run this without a card. Other members ask once; a from-now-on approval makes future calls seamless. Connecting a connector still needs the OAuth/connect card (request≠grant).]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reviseNorevise:true with decision:"denied" sends the card back to the producing agent to redo with your feedback — nothing publishes. Re-runs the originating activity and re-surfaces a corrected card. Omit/false for a plain rejection (learn-only). Only valid alongside decision:"denied" — any other decision is rejected. Prefer plain-string feedback; blank is ok (defaults to "Please revise").
item_idYesUUID of the Command Center card to decide on
decisionYesThe decision: approved, denied, snoozed, or dismissed (dismissed = honest acknowledgment of a blocked_on_you card — never resolves it)
feedbackNoWhat to change when revise:true — preferred plain string telling the producing agent what to fix. Also accepted under aliases: reason, revision_feedback, user_feedback, comment, notes (and shallow nested {text}/{content}). Optional: blank revise feedback defaults to "Please revise" (same as the browser card). Optional on plain deny/approve.
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
grant_modeNoCapability-approval (mcp_tool_call) cards only: 'once' runs the approved call WITHOUT granting the capability for future calls (the next identical call asks again); 'standing' (the default when omitted) runs it AND grants it so future calls run without asking. Ignored on every other card type.
hold_untilNoLoop-health, once-play timeout, hired-job, or quiet-alarm hold: future ISO date or YYYY-MM-DD that would prove the card wrong. Required with decision snoozed on those classes.
spin_off_kindNoSplit residual kind (default feature). Only used when spin_off_title + spin_off_description are set.
spin_off_titleNoSplit residual: one-line title for ONLY the novel half (requires spin_off_description). Closes the original card without re-building the mixed ask; mints a separate FO product-request card for this residual.
hired_job_actionNoUnclosed hired-job cards only: retry the first job once. Required with decision approved on that class. Dismiss is not legal. Accepted briefs are not graduation.
once_play_actionNoOnce-play timeout cards only: retry the same play once, or retire it. Required with decision approved on that class. Dismiss is not legal.
conforming_summaryNoOptional one-line name of the already-decided/conforming half (audit stamp on the closed card).
loop_health_actionNoLoop-health cards only: bind or retire ONE named loop. Required with decision approved on that class. Dismiss is not legal.
agent_outcome_actionNoPlaying-house / thrash / agent_outcome_flag alarms only: pause plant work. Required with decision approved on that class. Stretch and Dismiss are not legal.
spin_off_descriptionNoSplit residual: full description for ONLY the novel half (requires spin_off_title). Do not restate the already-decided conforming half as work to build.

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does well by warning that this 'initiates a multi-step agent process' and mentions trust scoring, autopilot evaluation, skill learning, and deliverable queue progression. It also explains the sensitive-tier permission nuance. It does not address reversibility or what is returned, keeping it below a 5.

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 appropriately sized for a complex tool and front-loads the core action before side effects and usage rules. The bracketed authorization note is dense but relevant, though the sentence about 'trust scoring, autopilot evaluation, skill learning, and deliverable queue progression' could be tightened.

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 15 parameters, conditional class-specific actions, and no output schema, the description provides enough high-level context to make the tool's role and side effects clear, while the schema handles the parameter-level details. It does not mention how to list Command Center cards first or describe the return value, but these are minor gaps.

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%, and each parameter already has detailed semantic descriptions. The tool description adds only high-level context for the split behavior, so it does not significantly expand on what the schema already provides.

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

Purpose4/5

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

The description opens with a specific verb and resource: 'Approve or deny a Command Center card,' and adds the split-card behavior, making the core function clear. It does not explicitly distinguish this from sibling tools like approve_pipeline_item or confirm_mcp_approval, so it stops short of a 5.

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 bracketed note gives concrete usage context: company managers can run this without a card, other members need a one-time ask, and connector OAuth still requires the connect card. This provides a clear authorization boundary, though it does not name alternative tools explicitly.

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