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Drillable

by com.drillable

Ask to hear when a missing answer lands

notify_when_held

Register your user's standing interest in a question the corpus can't answer yet: when it becomes answerable, they get one email. Call this ONLY when the user themselves asked to be told — ask them first, this session, and use the email they give you now; never volunteer an address you hold from context or memory. One call per question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
emailYesThe email the user gave you this session for this purpose.
queryYesThe question to follow, as the user asked it.

TDQS

A4.5/5.0
Behavior4/5

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

No annotations present, so description carries full burden. It discloses that one email will be sent when answerable and requires explicit user consent. However, it doesn't clarify behavior if called multiple times for same question beyond 'one call per question'.

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?

Description is 4 sentences long, front-loaded with purpose, then usage rules. No wasted words, but could be slightly more concise without losing clarity.

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 simple 2-parameter tool with no output schema, description covers purpose, usage constraints, and behavior. Lacks explicit mention of return value, but the email notification implies no immediate data return.

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 covers all parameters with descriptions. Description adds critical usage context: email must be from this session, query is verbatim from user. This adds practical meaning beyond schema, earning above baseline.

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?

Description clearly identifies the action ('register interest') and the resource ('question the corpus can't answer yet'). It distinguishes from sibling tools, which are generic operations like call or compute, by specifying a notification-after-answer scenario.

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 states when to use ('ONLY when the user themselves asked to be told'), when not to use ('never volunteer an address from context or memory'), and limits ('one call per question'). Provides clear context and exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Drillable toolsInspect
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TDQS

A4.3/5.0
Disambiguation4/5

Each tool has a distinct primary role—describe discovers, search/lookup/enumerate retrieve different shapes, compute aggregates, drill fetches addresses, verify checks claims, and notify_when_held tracks gaps. The main ambiguity is that compute and drill can both serve count/aggregate questions, though the descriptions do cross-reference each other to guide selection.

Naming Consistency4/5

Eight of the nine tools follow a clear lowercase single-word verb pattern: call, compute, describe, drill, enumerate, lookup, search, and verify. notify_when_held breaks that pattern with snake_case and a multi-word verb phrase, creating a minor but noticeable inconsistency.

Tool Count5/5

Nine tools is a well-scoped count for a knowledge retrieval and verification server. Each tool earns its place and the set avoids both bloat and thinness.

Completeness5/5

The tool surface covers the full intended lifecycle: discovery, search, glossary lookup, complete-set enumeration, aggregation, address-based drilling, claim verification, and registering unanswered questions. Abstentions and gap logging are built into misses, and describe/call unlock domain-specific verbs, so there are no obvious dead ends.

Resources