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freedom-mcp

by com.getfreedomos

scan_product_signals

Scan a company for product-system bugs and unlocks (failed/timed-out activity runs, blocked_on_you cards, open error agent_feedback) and return ranked product-request candidates for the FreedomOS product team. Use when the product team is hunting class bugs/unlocks across a portfolio tenant (dry-run by default; set file_top_n to file up to 5 bug cards). Does NOT invent feature fantasy — bias is bugs/unlocks only. For FreedomOS product-inbox members only.

[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
companyIdNoFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
company_idYesTenant company_id to scan (e.g. …_the-optimal-company- or a portfolio co).
file_top_nNoIf >0, file the top N signals as product_request decision cards (max 5). Default 0 = dry-run only.
lookback_daysNoHow far back to look (1–60, default 14).

TDQS

A4.3/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It thoroughly discloses behavioral traits: write-tier requiring potential approval, dry-run default, limit on file_top_n (max 5), bias toward bugs/unlocks only, and specific scanning scope (failed/timed-out runs, blocked cards, open error feedback). This is comprehensive and transparent.

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 informative and well-structured, with the main action front-loaded. It includes necessary details without being overly verbose. However, it could be slightly more concise by removing some redundancy (e.g., repeating 'dry-run' in both the description and parameter context).

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 complexity (4 parameters, no output schema, no annotations), the description covers the essential information: purpose, inputs, behavior, limitations, and approval notes. It lacks a detailed description of the return format, which is somewhat mitigated by stating it returns 'ranked product-request candidates.'

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 the baseline is 3. The description adds minimal extra meaning beyond the schema descriptions. It repeats the dry-run default and file_top_n limit, but these are already implied by the parameter descriptions. No additional semantic value is provided for parameters.

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's purpose: scanning a company for product-system bugs and unlocks, and returning ranked product-request candidates. It specifies the target audience (FreedomOS product team) and distinguishes itself from feature creation by explicitly stating it does not invent feature fantasy.

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 provides explicit usage context: 'Use when the product team is hunting class bugs/unlocks across a portfolio tenant.' It also mentions dry-run default and the file_top_n parameter to file cards, and clarifies access restrictions ('For FreedomOS product-inbox members only'). However, it does not explicitly compare to sibling tools, which would earn a 5.

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