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freedom-mcp

by com.getfreedomos

archive_pipeline

Archive (or restore) a content pipeline — flips is_active off/on, mirroring the Content Pipeline UI's soft-delete/restore. No data is deleted or cascaded. Use when the user says "archive this pipeline", "pause my newsletter automation", "turn off this pipeline", or "bring back my archived pipeline" (pass restore:true).

[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
reasonNoOptional. Why this pipeline is being archived or restored.
restoreNoSet true to REACTIVATE an archived pipeline instead of archiving it. Default false (archive).
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
pipeline_idYesID of the pipeline to archive/restore (get from list_pipelines)

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It clearly states 'flips is_active off/on' and 'No data is deleted or cascaded.' It also mentions the approval requirement. Missing info on return value or error behavior, but core effects are 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?

The description is two short paragraphs with no redundant text. It front-loads the main action, provides usage examples, and includes a necessary approval note. Every sentence is justified.

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 simplicity (toggle, no output schema), the description covers the essential behavior and usage. However, it does not explain expected return or error states, which could be helpful for an agent.

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% and descriptions are clear. The description adds value by specifying that pipeline_id comes from list_pipelines and clarifying restore parameter semantics. This goes beyond the schema alone.

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 archives or restores a pipeline by toggling is_active. It distinguishes from other tools by explicitly likening it to the UI's soft-delete/restore. Example user phrases further clarify the purpose.

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 scenarios (archive, pause, restore) and notes the restore:true parameter. The write-tier approval note adds context. However, it does not discuss fallback or error cases, or explicitly contrast with sibling tools like update_pipeline.

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