Skip to main content
Glama

get_team_pulse

Get a real-time snapshot of team output volume, pending approvals, and founder load. pending_cards is the LIVE open queue (includes cards older than days). activity_runs and approval_velocity are the last N days only. Shows cards per agent, approval velocity, oldest pending items, and load trends. Use this to detect if the founder is being overwhelmed, if agents are producing too much or too little, or if cards are piling up without action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback window in days for activity_runs and approval_velocity only (default: 7). pending_cards is always the live queue.
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.
company_idNoCompany ID to check. Usually auto-injected from context.

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It clearly explains the temporal behavior: pending_cards is the live open queue including cards older than days, while activity_runs and approval_velocity cover only the last N days. It does not mention permissions or rate limits, but this is a read-only snapshot tool and the key behavior is well disclosed.

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 three dense sentences with no filler: core purpose is front-loaded, time-window nuances follow, and concrete use cases close the description. Every sentence earns its place.

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 getter with no output schema, the description enumerates the major return areas—cards per agent, approval velocity, oldest pending items, and load trends—and gives concrete diagnostic scenarios. Required companyId is documented in the schema, so nothing essential is missing for invoking the tool correctly.

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%, so the baseline is 3. The description mostly restates what the schema already says about days applying only to activity_runs and approval_velocity and pending_cards being the live queue. It adds output context, but that is not fresh parameter-level meaning.

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 opens with a specific verb and resource: 'Get a real-time snapshot of team output volume, pending approvals, and founder load.' It then enumerates concrete outputs like cards per agent, approval velocity, oldest pending items, and load trends, making it easy to distinguish from sibling getters such as get_team_members or get_agent_performance.

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 explicitly states when to use the tool: 'Use this to detect if the founder is being overwhelmed, if agents are producing too much or too little, or if cards are piling up without action.' It does not name alternatives or provide when-not-to-use guidance, so it falls just short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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