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test_planner_trigger

Dry-run the Dynamic Planner's escalation judge: would these messages be offered a step-by-step plan? Use it after editing the agent's task, since the task text is the business-domain gate — a vague task lets out-of-domain requests through, a narrow one turns real customers away.

messages: the user's turns in order; the LAST one is treated as the current turn and the rest
as that user's earlier messages (same window the live judge sees). samples>1 re-runs the judge
to show stability (it is a probabilistic call). expect: pass true/false to get `matched`.
Nothing is stored — no session, no enrollment. Tokens count toward the tenant quota (kind=planner).

Returns {triggered, samples, goals[], domain, matched}. Reads the judge only: whether the user
then ACCEPTS the offer is a separate, user-controlled step.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentYes
expectNo
samplesNo
messagesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A5/5.0
Behavior5/5

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

With no annotations provided, the description carries full burden and does an excellent job: it discloses that nothing is stored, no session/enrollment is created, tokens count toward quota, and that the judge is probabilistic. It also states the tool only reads the judge and does not affect user acceptance.

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 front-loaded with a clear purpose statement, then organizes parameter explanations in a compact paragraph, and ends with return values and scope. Every sentence contributes essential information without redundancy.

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?

Despite having an output schema, the description still enumerates the return fields and explains the business-domain gate concept. It gives enough context for the agent to understand when and how the judge works, including probabilistic behavior and the separate acceptance step.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description thoroughly explains messages (last is current, rest are earlier), samples (re-runs for stability), and expect (pass true/false to get matched). Agent is the only parameter not directly explained, but it is obvious from context and the schema title.

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 starts with a specific verb and resource: 'Dry-run the Dynamic Planner's escalation judge' and asks a concrete question. It clearly distinguishes this tool from similar ones like test_skill_trigger by focusing on the planner and the escalation judge.

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?

It explicitly tells when to use the tool: 'Use it after editing the agent's task' and explains why. It also clarifies what the tool does NOT do—does not determine if the user accepts the offer—which provides an important exclusion boundary.

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

Tools are mostly distinct by domain and action. A few pairs like add_knowledge_file vs add_knowledge_text or build_knowledge_index vs patch_knowledge_index could cause confusion, but descriptions clearly differentiate them.

Naming Consistency4/5

The vast majority follow a consistent verb_noun snake_case pattern (create_*, list_*, get_*, update_*). A few outliers like tenant_info, usage_stats, and page_context_stats are noun-first, deviating slightly from the otherwise uniform scheme.

Tool Count1/5

With 50 tools, this is a very large surface that exceeds typical well-scoped server sizes. Even for a broad platform management API, the sheer number makes it heavy and potentially overwhelming, matching the '50+' extreme mismatch category.

Completeness2/5

The server covers creation, reading, updating, and listing for most resources but lacks any delete operations (no delete_agent, delete_knowledge_base, delete_skill, delete_share, delete_storyline, delete_page_context). This is a significant gap in lifecycle coverage that will force agents to work around missing functionality.

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