freedom-mcp

set_attention_budget

Set the founder's attention budget — the maximum pending review cards before they are 'overloaded' (a whole number 1–100; default 7) — for a manager or the founder. Use when the founder (or a manager on their behalf) wants to raise or lower their overload threshold (e.g. "set my overload threshold to 10", "I can handle more pending cards before you flag me", "lower my attention budget to 5"). This is the founder's OWN constraint, so it is gated: an autonomous agent CANNOT change it (surface a recommendation instead); only a human-present company manager can. Always call get_attention_budget first and explain why a change helps the founder.

[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
`note`	No	Optional rationale for the change (stored with the budget).
`companyId`	Yes	FreedomOS company id to act within (you must be a member). Required for company-scoped tools.
`max_pending_cards`	Yes	The new ceiling: pending review cards before the founder is overloaded (whole number, 1–100).

TDQS

A4.9/5.0

Behavior5/5

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

With no annotations, description fully carries the burden. It discloses the gated nature (autonomous agent cannot change), requires human manager, mentions approval modes (first use may require approval, from-now-on vs just-once), and advises explanation. This is highly transparent.

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?

Description is well-structured: starts with definition, then usage context, then constraints, then safety note. Every sentence adds value; no redundant or unclear phrasing. Concise yet thorough.

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

Completeness5/5

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

For a setter tool with no output schema, the description covers purpose, parameters, constraints, and usage advice. It does not need to explain return values. The information is sufficient for an agent to decide when and how to invoke it.

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

Parameters4/5

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

Schema coverage is 100%, baseline 3. Description adds meaning by explaining max_pending_cards as whole number 1-100 with default 7, and note as optional rationale. It contextualizes the core parameter beyond schema, justifying one point above baseline.

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 sets the founder's attention budget, defines it as the maximum pending review cards before overload, and specifies the action (set) and resource (founder's attention budget). It also distinguishes from sibling 'get_attention_budget' by mentioning to call it first.

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?

Explicit usage guidance: when to use (founder or manager wants to change overload threshold), example phrases, what not to do (autonomous agent cannot change, only human-present manager can), and recommended prior step (call get_attention_budget and explain why). This is comprehensive.

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.

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