Meta Council

Create Saved View

create_saved_view

Save a named ticket filter, column, grouping and sort bundle so you can reopen it later or share it with a team. Saves the QUESTION, not an answer: the view is re-run against live tickets every time it is opened, so it never goes stale. The new view is private until you share it. Same endpoint the web app's save button uses. Requires authentication and the tickets:write scope.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes	What to call the view.
`columns`	Yes	Which ticket columns the view shows, in order. At most 20.
`filters`	No	Which tickets the view selects. Same filter vocabulary the ticket list accepts; omitted filters are unset.
`sort_by`	No	Optional ticket field to sort rows by.
`group_by`	No	Optional ticket field to group rows by.
`sort_dir`	No	Sort direction. Defaults to asc.	asc

Output Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes

TDQS

A4.4/5.0

Behavior4/5

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

With annotations all false, the description carries the full burden. It discloses that it saves a question, not an answer (views re-run on live data), that the view is private until shared, requires authentication, and needs the tickets:write scope. This goes beyond the annotations and gives actionable context about side effects and access.

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?

Three sentences, front-loaded with the purpose. Every sentence adds value: purpose, behavioral nuance, and access requirements. No redundancy or 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?

The description covers purpose, behavior, sharing, and authentication. With an output schema present, the need to explain return values is mitigated. It could mention how to reference the created view (e.g., returned ID), but output schema likely covers that. Overall, it is complete for an agent to decide and execute.

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%, so each parameter already has descriptive semantics. The description adds context that these parameters form a bundle (filter, columns, grouping, sort) and clarifies that filters use the same vocabulary as the ticket list. This adds meaning beyond the schema by explaining how parameters work together.

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 saves a named bundle of filter, columns, grouping, and sort for later reuse or sharing. It distinguishes from siblings like update_saved_view (which modifies) and execute_saved_view (which runs) by focusing on creation.

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?

Provides clear context on when to use: to save a view for later or share, and notes it is the same endpoint as the web app's save button. It does not explicitly mention alternatives like update_saved_view for editing, but the purpose and context make usage clear.

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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