Meta Council

Execute Saved View

execute_saved_view

Read-onlyIdempotent

Run a saved ticket view's stored filters against live tickets and return the matching tickets, the view that produced them, and group counts when the view groups. Results are always YOUR tickets: a shared view shares the question, not the answers, so opening a teammate's view runs it against your own work and never reveals theirs. An archived view is refused rather than executed. Returns the same payload the web app receives. Requires authentication and the tickets:read scope.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	How many tickets to return. Defaults to 200. The ceiling is above the ordinary ticket page size because group counts need to see more rows in one call than a paged list does.
`offset`	No	How many tickets to skip. Defaults to 0.
`view_id`	Yes	The view's id, from list_saved_views.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes

TDQS

A4.4/5.0

Behavior5/5

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

The description discloses behavior beyond annotations: it notes results are always the user's own tickets, that shared views do not reveal others, and that archived views are refused. It also states the return payload and required auth/scopes, adding transparency not fully captured by annotations.

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 front-loaded with the core purpose, but it repeats the phrase 'your tickets' and could be slightly trimmed without losing meaning. Still, it is well-structured and not overly verbose.

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?

It covers the core behavior, result semantics, edge cases (archived views), return payload, and authentication/scoping requirements, making it complete for the tool's complexity.

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?

The schema already provides descriptions for all three parameters (limit, offset, view_id). The description adds no extra meaning to these parameters, so it stays at the baseline for high schema coverage.

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 that the tool runs a saved view's stored filters against live tickets and returns matching tickets, which distinguishes it from sibling tools like get_saved_view or list_saved_views.

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?

It provides context on when to use (has a saved view and wants tickets) and clarifies semantics around shared and archived views, but does not explicitly compare with 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

Disambiguation5/5

Every tool targets a distinct resource and action, with detailed descriptions that clearly separate overlapping domains (e.g., consulting vs. marketing vs. outreach). Even within the same domain, tools like 'create_consulting_deliverable' and 'create_consulting_document_revision' are unambiguous due to their specific nouns.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (e.g., 'create_invoice', 'get_deal', 'list_agents'). The few exceptions like 'locus_determine_from_scores' still adhere to the verb_noun structure and do not break the pattern.

Tool Count1/5

With 124 tools, the server is massively over-scoped for typical MCP use. The tool count far exceeds the '50+ extreme mismatch' threshold, making it nearly impossible for an agent to efficiently navigate or select the right tool without extensive context. Even a large platform should consolidate or expose fewer tools.

Completeness5/5

The tool surface covers CRUD and lifecycle operations across at least 10 domains (sales, consulting, marketing, outreach, accounting, workflows, ticketing, API keys, feedback, platform metrics). Each domain appears to have no obvious gaps—e.g., invoicing includes create, update, send, mark paid, void; ticketing includes create, update, archive, dependencies, batch, scenarios, validation.

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