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get_partnership_pattern

Get a named strategic AI partnership pattern with its plain-language description, example clauses, kill-list moves, scholarly anchors, and real-world precedent anchors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pattern_slugYesPattern slug. Examples: compute-backed-strategic-invest, hyperscaler-exclusive-then-multi-home, oem-with-third-party-ai-model, capacity-reserve-agreement, compute-for-equity, sole-source-ip-grant, sovereign-trade-capacity, white-label-metered.

TDQS

A4/5.0
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 discloses the return contents in detail, which is valuable for a read-only getter. However, it doesn't mention error handling (e.g., unknown slug) or any side effects. Given the low-risk read nature, this is adequate and adds context beyond a bare 'Get pattern'.

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 a single front-loaded sentence that states the action and enumerates the result components. Every phrase contributes to understanding what the tool returns. No filler or repetition of schema details.

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?

For a single-parameter tool with no output schema, the description is reasonably complete: it lists all the elements returned and the parameter is fully documented. However, it lacks explicit guidance on when to use this tool versus siblings, and the absence of an output schema means the description's list must suffice. It could mention behavior for unknown slugs, but that is a minor gap.

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 coverage is 100% with a descriptive property and examples. The description adds little beyond calling the pattern 'named', which ties to the pattern_slug. Per calibration, baseline is 3 when schema fully documents parameters, and the description does not compensate or go beyond it.

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 identifies the tool as retrieving a named pattern, enumerating its contents (plain-language description, example clauses, kill-list moves, scholarly anchors, precedent anchors). This distinguishes it from siblings like get_partnerships_by_pattern, which likely returns partnerships matching a pattern rather than a single named pattern.

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

Usage Guidelines3/5

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

No explicit when-to-use guidance or alternative references. The description implies this tool is for fetching a specific pattern by slug, but it doesn't say when to prefer it over get_partnerships_by_pattern or search_corpus. This is typical of a simple getter but falls short of the 4 or 5 standard.

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

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct entity: framework versions, partnership patterns, partnerships by pattern, vendor commitments, and regulatory provisions. No overlap in purpose.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case (get_*, search_*). Predictable and uniform.

Tool Count5/5

5 tools is well-scoped for the domain of AI governance tracking. Each tool covers a distinct aspect without bloat.

Completeness4/5

The set covers frameworks, partnerships, vendor commitments, and regulatory search. A minor gap is the absence of a tool to retrieve details of a single partnership by name, but core workflows are supported.

Resources