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get_attention_quest

Speech-safe Quest Log strip for voice CoS (N5). One call returns: primary next move (featured Command Center card when companyId given, else top host that needs you), needs_you hosts, running host count, and work_units (sessions · lab_work cascade · ship-seat open PRs — same inventory as Quest Work rail). Prefer this when the operator asks "what's next", "what's in Quest Log", "what needs me", "where is PR N", or after open — instead of inventing SPA state. Speak spoken / spoken_label / speak_first. For ship-seat PR titles match work_units.label / work_units.pr.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyIdNoOptional active company for featured card pick. Omit for host-only board (still returns needs_you + running).
company_idNoAlias of companyId

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It thoroughly describes the return payload (primary move, needs_you, running count, work_units) and notes the speech-safe nature and how to handle spoken labels. It does not explicitly state it is read-only, but the 'get' prefix and return-focused wording imply a non-mutating operation. It lacks discussion of errors or permissions but is otherwise transparent about behavior.

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 dense but well-structured: it opens with a concise purpose sentence, then lists components, then gives usage triggers and output handling. No wasted words; each sentence serves a purpose. Slightly long but appropriately detailed for the tool's complexity.

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?

With no output schema, the description fully explains return values: it enumerates the four components and provides details on how to interpret them (e.g., 'Speak spoken / spoken_label / speak_first' and matching PR titles to work_units fields). It also covers the optional parameter behavior. Given all this, the description is complete for effective use without additional context.

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%, but the description adds meaning beyond the schema by explaining that companyId controls the featured card selection ('when companyId given, else top host that needs you') and that omitting it yields a host-only board. It also clarifies the alias company_id. This goes beyond the schema's basic descriptions, adding actionable context.

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's purpose: a speech-safe quest log strip that returns primary next move, needs_you hosts, running host count, and work_units. It distinguishes from siblings by specifying it returns data from the Quest Work rail and advises against inventing SPA state, making its scope unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly lists operator asks like 'what's next', 'what's in Quest Log', 'what needs me', and 'where is PR N' as triggers, and signals when to use it 'instead of inventing SPA state'. It also explains the companyId parameter's effect, giving clear when/why guidance.

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.

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