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update_pipeline_style_guide

Manually add a style rule to a pipeline. Use when user says "always use bullet points", "never include hashtags", "keep it under 100 words", "use more casual tone", or gives general content preferences.

[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
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
style_ruleYesThe style rule to add (e.g., "Use bullet points for lists", "Keep under 150 words")
pipeline_idYesPipeline ID (get from list_pipelines)
output_formatYesWhich format this rule applies to: changelog, social_post, team_update, newsletter, report

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description partially covers behavior by noting the approval process for first use and ongoing use. It does not disclose whether adding a rule overrides existing rules, reverts, or has other side effects. Some behavioral context is provided but not exhaustive.

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 two sentences plus a brief note. It is front-loaded with the core action, includes examples, and provides essential behavioral context without unnecessary fluff.

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 has 4 required parameters, no output schema, and no annotations, the description covers purpose, usage, and approval behavior. It lacks details on return values or whether the rule replaces existing ones, but it is fairly complete for a straightforward add-rule tool.

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 description coverage is 100%, so baseline is 3. The description adds value by giving concrete examples for style_rule and output_format parameters (e.g., 'Use bullet points', 'changelog'), which helps the agent select appropriate values beyond the schema's generic descriptions.

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 clearly states 'Manually add a style rule to a pipeline,' which is a specific verb+resource. Examples like 'always use bullet points' help clarify the tool's purpose, but it does not explicitly differentiate from sibling tools such as update_pipeline, though the intent is distinct.

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 guidance on when to use the tool ('Use when user says...') with concrete examples. It also includes note about write-tier approval requirements. However, it lacks explicit instructions on when not to use it or alternatives.

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