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run_intent_pack

build_intent_queries + find_conversations for every phrase, merged and deduplicated, newest first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
jobsNo
contextNo
productNo
categoryNo
competitorsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations the description carries full disclosure duty, and it does contribute real behavioral facts: results are merged, deduplicated, and ordered newest first. It is silent on everything else an agent wants for a 6-parameter aggregation call — rate limits, permissions, how the two upstream queries are scoped, and what the response actually contains.

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?

One compact sentence, correctly front-loaded with the composed action before the merge/dedup/order qualifiers, and no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an aggregating tool with six undocumented parameters, no annotations, and no output schema, the definition is far too thin: it never defines what qualifies as a 'phrase', how the parameter set drives the two underlying queries, or what a merged/deduplicated result looks like. Only the ordering and dedup semantics are covered.

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

Parameters1/5

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

Schema description coverage is 0% across six parameters (days, jobs, context, product, category, competitors), and the description explains none of them — its only temporal hint, 'newest first', is about output ordering, not the 'days' window. Nothing compensates for the undocumented schema, so an agent cannot tell which inputs scope the intent queries versus the conversation search.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

It states a concrete composition: run build_intent_queries plus find_conversations, then merge, deduplicate and sort by recency, and it names the two sibling tools it wraps, which separates it from build_intent_queries and find_conversations. However the phrase 'for every phrase' never maps onto any actual input field, so the scope is partly ambiguous.

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?

By describing itself as the union of two named sibling tools, it implies usage: reach for this when you want both result sets combined in one pass instead of calling each separately. There is no explicit when-not guidance or statement of what you lose (e.g., per-tool filtering) by choosing this over the siblings.

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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